These days, Java is mostly used in greenfield software that has to be very reliable, very performant, and last for many years. So it's often the first choice for banking, telecom, finance, government, defence, manufacturing control, logistics and shipping, media streaming, retail, hospitality, healthcare etc.. It's usually not a first pick for more exciting software, such as Python type checkers, JS bundlers, or TUI file managers.
I think of Java/Kotlin and Spring as a secret weapon for startups. My workplace was a startup 5 years ago and it's amazing how things just worked as expected, leaving us more time to focus on the product. We have tried a few alternatives over the years, such as a few services in Rust, but the people who implemented those have usually seen the advantage of using a stable ecosystem after a few years. It's unfortunately something you need to experience yourself instead of being told by someone else.
First, they do. Second, most software is not only not produced by software startups, it's not even produced by software companies. Do you know how much software a bank, or a credit card company, or a telecom provider, or a car manufacturer (like BMW), or a shipping company (like FedEx), or a defence company (like Boeing), or a large retailer (like Walmart) write in house?
Wasn't the discussion about greenfield projects? Or by greenfield do you mean internal greenfield projects at existing companies that already use Java?
i can't speak to the others but banking and healthcare is virtually all java top to bottom. The big healthcare EMR/EHR systems are Java and every bank i've ever worked with (i use to do a lot of integrations with the big banks) was all Java. I have friends in those areas and whenever they start up a new project it's still always Java since that's where their skills are and what's on the "approved tech." list.
Until quite recently, the reasonably feature complete open source libraries available for things like DICOM or HL7 were old C/C++ libraries, Java, and C#. That often created a choice between Java and C#. People not doing Windows based development tend not to be interested in C#.
We embedded angular in our old Java client for hospitals. The user thinks he just opens a new window, but it's chrome in Java, which opens angular frontend, for our Java backend.
They lack in performance, stability (compatibility), observability (telemetry), productivity, or some combination thereof. They are chosen, of course (especially C#; Go and Rust are far behind), but not as much as Java.
Saying that Go lacks in those is just showing how people are making software those days. It’s just terrifying.
As to Rust - we all, hopefully, agree that it’s great language, but not for some startup making websites or Mongo based, boring backends. It’s great for the stable, system level products.
I don't know what compiler and GC quality has to do with how people are making software these days, and I don't think state-of-the-art optimising compilers and GCs are terrifying at all. Go opts for more traditional, simpler algorithms under the assumption that for many purposes they're good enough. That may be so, but sometimes workloads really are very demanding, and you need the best performance.
and the costs they are willing to pay. Go/Rust just kill everything else (except maybe C++) for performance and resource needs. JVM requires so many resources just to run small apps.
Quite the opposite, and the reason is that you can't extrapolate from small programs to large ones. Low-level languages (like C++) incur some significant overheads as they grow large (because of essential constraints of low-level languages that prevent them from doing certain optimisations that matter mostly in large programs), and these are exactly the overheads the JVM is designed to reduce. In small or short-lived programs, the situation is different, because Java does have some warmup costs and some fixed memory overheads that matter when you're small or short-lived. Go's compiler and GC are pretty basic, and are certainly good enough for smaller things, but don't scale as well to high workloads. Just the other day a colleague tested Caffeine, an old and well-established Java caching library, and Moka, a Rust caching library with the same workload. Caffeine had the same latency as Moka across all percentiles at twice the throughput.
> Caffeine had the same latency as Moka across all percentiles at twice the throughput.
Caffeine's next release has roughly 25% higher read throughput, with unchanged write throughput, thanks to fixing a false sharing mistake. That won't be visible in real workloads, but is fun nonetheless (500M reads/s on 8 cores).
I use Java every day but just to point out that your info about Go‘s GC seems out of date. They switched to Green Tea in 1.25 (I think?) - new GC that even has AVX-512 optimizations. Not sure what you mean by basic about the compiler but it‘s very fast and supports a large set of platforms. That‘s not basic to me.
We are using JDK25 and are considering rewriting parts of our product to Go because of lower memory pressure and faster startup time, i.e., cloud friendly. I actually love both languages.
> I use Java every day but just to point out that your info about Go‘s GC seems out of date.
I'm well aware that Go's GC has improved, but the moving algorithm was designed not just to be fast for a GC, but to be faster than no GC. So Go's new GC is good - for a mark and sweep collector. But it can't compete with a moving collector (the only thing that can is arenas, which are user-friendly only in Zig).
> We are using JDK25 and are considering rewriting parts of our product to Go because of lower memory pressure and faster startup time, i.e., cloud friendly.
Java probably will never have perfect warmup, but it's getting very good - https://openjdk.org/jeps/544 - probably in JDK 28.
As for memory, I think Java's memory strategy is generally misunderstood and I've given a talk about it: https://youtu.be/xr73mR7ii9M The footprint overhead exists to compensate for CPU utilisation when the CPU utilisation is more disruptive than memory usage. The problem is that many Java developers - and I'm not blaming them - don't understand this tradeoff and how to configure the JVM for optimal resource usage, but the great news is that a solution is coming soon, too - https://openjdk.org/jeps/8377305 - also possibly in JDK 28.
So it's very likely that both of these issues will be resolved six months from today, and you'd still get to enjoy better performance and telemetry than all alternatives.
Go's compiler is fast because it doesn't do as many advanced (read: computationally expensive) optimizations as other compilers do. No clue about Green Tea and how awesome it is :-).
Lower memory pressure is certainly a difficult thing to beat Go at, Java (OpenJDK) is probably never gonna get there. You get a lot of other stuff, like better peak performance, instead.
Btw, have you tried Leyden/AOT for better startup times? Curious about your experiences with that.
> Which specific optimizations are you referring to?
A JIT with speculative optimisation and a moving GC.
There are two constraints in low-level languages that trump any of their performance goals, one technical and one a matter of preference.
The technical limitation is that they must use stable pointers (because they need to be low-level and so having an FFI layer that separates "hardware pointers" from "language pointers", as we have in Java defeats their main purpose). This means that you need to translate data storage or code storage to hardware addresses, and that interferes with both moving collection and with JIT compilation.
The other constraint is that low-level languages value worst-case performance over the average-case and even amortised performance. These languages prefer an operation (e.g. dynamic dispatch) to be slow as long as it's never too slow. With a JIT (and I describe more later), virtual dispatch can be super-fast almost all the time, but occassionally, you'll hit a trap because the speculation was wrong, and then you need to deoptimise and recompile.
> In my experience, this is largely a myth; compared to Rust, you actually get even faster code right away.
We wouldn't be doing it in the first place if it was a myth. In a low-level language, you can get very fast code if you do some manual optimisations, but they don't easily scale as the program grows and evolves, because they're viral. The two most basic examples are dynamic dispatch (which is the most general mechanism, which scales the best in terms of program evolution) and shared heap objects (again, the most general mechanism). These become more common and less easily avoided over time, and they're slow in low-level languages because of the constraints I mentioned.
That low-level languages make it harder and harder to preserve good performance over time as they evolve and grow is a problem familiar to those who've worked for years on large software written in a low level language (as I have). The JVM was designed, among other things, to solve this performance problem in large programs.
> JIT is effective for languages where the source code lacks sufficient information (dynamic typing, where anything can be null).
A JIT can make such languages decently fast, but that's not how it's used in Java. In Java it is used for speculative optimisation, which allows far more aggressive optimisation than an AOT compiler can do. E.g. by default, Java inlines and specialises virtual calls 15 levels deep. An AOT compiler can't do that or its code will explode. We get around it with selective use of templates in C++ (or comptime in Zig), but it has to be selective, and it's viral.
> A JIT with speculative optimisation and a moving GC.
Idiomatic Rust, through its concepts of ownership and borrowing, encourages a pattern where you receive data as an argument or create it directly, perform operations on it, and then discard it via RAII. This bears some resemblance to functional programming. This approach does not apply to buffers of unknown size, which still require heap allocation; unfortunately, Rust lacks automatic buffer reuse. However, such optimization is theoretically possible. The stack is definitely faster than anything else.
> This means that you need to translate data storage or code storage to hardware addresses, and that interferes with both moving collection and with JIT compilation.
You don't need GC if you allocate data on stack. You also do not need to dereference the pointer.
> dynamic dispatch
You mentioned templates. In Rust, traits that are monomorphized - much like templates-are the standard approach; using vtables or `dyn trait` is a relatively rare use case. This stems from the fact that all code is known at compile time and there is no dynamic loading, allowing the compiler to eliminate polymorphism from the code entirely.
> and shared heap objects
This might be considered convenient, but in my view, it also leads to code that is harder to maintain when objects can be modified from multiple places. However, I think that is outside the scope of the current discussion.
> We get around it with selective use of templates in C++ (or comptime in Zig), but it has to be selective, and it's viral.
Yes, monomorphization is the default solution in Rust. It is not always viral either, because when using it, you often define specific types, and they do not spread beyond that scope.
I suppose you could say that the programming style I am talking about is complex, inconvenient, unmaintainable, and so on. What I mean is, assuming this programming style is sufficiently convenient—and perhaps even has its own advantages - then none of the optimizations you listed offer an edge, and the Rust code will definitely be faster.
> However, such optimization is theoretically possible. The stack is definitely faster than anything else.
What you're describing isn't a stack, but an automatic arena, and this optimisation is easier to do in Java. It's easier to do in Java because it requires setting a "current arena" or inlining, both of which Java can do more easily, and then either the arena will be heap allocated (which will be slower in Rust) or associated with the thread, which is not something low-level languages tend to do.
> You don't need GC if you allocate data on stack. You also do not need to dereference the pointer.
Moving collectors don't need to dereference anything (they don't know and don't want to know when an object is "dead"), and stack allocation works in both languages, only, as you pointed out, is not quite general (not every data structure with a known lifetime can be allocated on the stack).
> You mentioned templates. In Rust, traits that are monomorphized - much like templates-are the standard approach; using vtables or `dyn trait` is a relatively rare use case. This stems from the fact that all code is known at compile time and there is no dynamic loading, allowing the compiler to eliminate polymorphism from the code entirely.
Sure, except Java does this automatically, and it can do it more aggressively. Dynamic dispatch is rare in low-level languages because it's expensive in those languages. But it's not easy to avoid as programs get larger. That is exactly one of the problems in large programs that the JVM set out to solve.
> This might be considered convenient, but in my view, it also leads to code that is harder to maintain when objects can be modified from multiple places. However, I think that is outside the scope of the current discussion.
I agree that whether it has downsides is outside the scope of this discussion, but the point is that as programs evolve and grow, the abstractions tend to be more general, and low-level languages suffer from "abstraction cost", where the more general abstraction (which becomes more common over time) is more expensive. Again, this is exactly why large C++ programs suffered from performance issues and what the JVM tried to address.
> Yes, monomorphization is the default solution in Rust.
... and in C++. But it is viral, and Java monomorphises without suffering from "zero overhead abstractions".
The ability to move pointers, both to data and to code, opens up the possibility of using JITs and moving GCs, which are very powerful optimisations. A JIT does impose two further tradeoffs (aside from the need for an FFI layer), though, which are warmup and the possibility of deoptimisation. We can now cache the generated machine code from one execution to another (https://openjdk.org/jeps/544), but the possibility of deoptimisation remains (in fact, it's what enables the aggressive speculative optimisations), which means you gain average (or even amortised) performance at the cost of the worst case.
Anyway, the JVM was designed as a solution for the performance issues low-level languages suffer from as programs grow and/or evolve. It comes with tradeoffs, but those most affect small or short-lived programs.
The thing to remember is that low-level languages are not optimised for performance but for low-level control (i.e. pointers are direct addresses etc.). Such control can translate to good performance when programs are small (see next) but it becomes a practical hindrance to performance when they're large.
> I suppose you could say that the programming style I am talking about is complex, inconvenient, unmaintainable, and so on. What I mean is, assuming this programming style is sufficiently convenient—and perhaps even has its own advantages
That advantage is a performance advantage. The question isn't "does there exist (in the mathematical sense) some program that is fast?" but "how fast is the program we can write within the budget we have?" When programs are small, manual optimisation is practical; when they grow large - not so much. And that's excluding the matter of a moving collector, which is just hard to compete with on speed regardless of program size, unless you use areans, but they're not at all easy to use in most low-level languages except Zig.
> and the Rust code will definitely be faster.
This is true only in the abstract mathematical sense. The reason we don't write programs that we want to be fast in Assembly (which is faster than anything in the same sense: for any program in any language, there exists and Assembly program that's at least as fast) is not because other languages are fast enough, but because in practice the programs we can actually write in the budget we have will be faster than the Assembly programs we could write. Of course, that could change when AI is able to generate perfect low-level code, but when that happens, it might as well generate machine code directly.
I think you have a biased view. The number of stuff written in Rust in the last couple of years has absolutely exploded. For example, I see a lot of projects now that provide SDKs in Rust but don’t bother with Java. And I say this as someone who still writes most of my code ( or tell my LLM to write) in Java.
There's a difference between number of programs and number of LOC (the latter is related to the number of people involved). I am not aware of any SDK targeting the industries I mentioned that "doesn't bother with Java". It's not only a popular choice in those industries, it's not only among the top choices, but it's the top choice by a large margin. Look at wanted ads in those industries to see that. Overall, there are only two languages as popular as Java or more, and they are JS and Python: https://www.devjobsscanner.com/blog/top-8-most-demanded-prog...
Yeah I mean he literally works on Java at Oracle, so may just be a little biased.
Doesn't bother to disclose it of course, because what, you don't check everyone's profile in every discussion to make sure they're not biased? What, you don't just know who every user on this site works for? You dummy you :)
It's disclosed right there in my profile (I don't see your professional affiliation disclosed in your comment; or your profile, for that matter). Of course, I, like other runtime and compiler people, joined the Java team because we wanted to work on the most advanced compiler and runtime tech. I perfectly understand people who want to work on smaller, newer, potentially insurgent products, but I took the chance to work on the cutting edge of compiler and runtime engineering, and Java is where it's at these days (I'm not saying it's the only one, but it's a very small club).
GP's snark is unwarranted, but it's probably good practice to disclose your professional affiliation explicitly in comments related to it, even if you have already disclosed it in your profile.
I was reading your comments on Java, nodding my head, upvoting, without checking your profile and realizing that you're a member of the Java team. Knowing that doesn't mean I now suddenly disagree with you or anything. But while in an ideal world it doesn't matter who's saying something when evaluating it, there's some human factors at play - I'd like to turn up my internal sense of skepticism when dealing with someone, effectively, selling something their salary depends on; even if you're being entirely earnest, it's ultimately a sales pitch, and I feel bamboozled for not recognizing it - that'd make me appreciate transparency.
(FWIW, even though I prefer being coy about my place-of-work, I have no professional relation to this conversation. I've never used Java in my 9-5 and I haven't even really used it in earnest since, like, version 5 back in high school. I think it's always been underrated by the hacker crowd, though!)
I agree that it matters, but whether and how to do it depends on the standard practice in the relevant forum. On HN, it's rare for people to disclose affiliation even in their profile, so I think I'm already better than the norm here on HN in that regard.
While Java can outperform Go in some cases, the situation is very much the opposite when it comes to Rust.
I also don't see the case for stability. Yes, if you're still on JDK 8, it would probably chug on for a couple of years. But we were talking about greenfield projects and newer JDK go EOL much faster. If you want patches, you'll have to run your app to a newer JDK, which may break a couple of things. Rust (within the same edition) or Go (within the same major version) break less than that.
As far as runtime compatibility goes, Rust and Go apps ship with the runtime. This can be better or worse for you, depending on what is your upgrade story, but I don't see a clear winner here. What I would give to Java over Rust is that you will have far fewer dependencies to take care of if you need to upgrade. But the same goes for Go.
For observability, I feel that with Rust you have a bit less that you need to observe (no GC to worry about). Tokio tracing is great, but observability requires a bit more effort. The go observability story is far worse. So Java probably has an edge here, but not something that ever felt like a game changer. My impression is that for most of the enterprise shops that love Java, observability means collecting unstructured log files through NFS and trying to find a needle in the haystack with primitive tools, but I've been out of touch with this world for a couple of years.
Productivity is something that is dead if you are AI-heavy. Sure, many shops are still wary about AI, and I totally get why, but this is a battle that's already been lost. Without AI, I would say I was about 3 to 4 times more productive in Rust than I was in Java, but ramping up that productivity took at least 1 year of practice. It's not time most companies are willing to spend. With AI, this doesn't matter anymore, for better or worse.
I'm not arguing that Java is not chosen often for greenfield projects. It's clearly extremely popular in many circles, especially outside startups and big tech. But I think the reason Java is chosen have little to do with the reasons you've mentioned above and more with organizational preferences.
> the situation is very much the opposite when it comes to Rust.
It isn't, and the problem isn't Rust specifically, but all low-level languages. They can offer very good performance (often better than Java) when small. But as they evolve over time, or are very large to begin with, they become much harder to keep performant. This is for pretty fundamental constraints of low-level language that I mention in another comment here, and this performance problem with large programs written in low-level languages was well known before Java even existed. The JVM was designed, at least in part, to address it.
One of the things that drew me to Java (from years of C++, even though I still work in C++ when I work on the JVM) is precisely how it addresses those performance issues we ran into with C++ five years into a project.
> As far as runtime compatibility goes, Rust and Go apps ship with the runtime. This can be better or worse for you, depending on what is your upgrade story, but I don't see a clear winner here.
I wasn't talking about "runtime compatibility" but of overall version compatibility. Java has an unmatched compatibility record - not perfect, but better than anything else (with at least a medium-sized standard library).
> For observability, I feel that with Rust you have a bit less that you need to observe (no GC to worry about).
Memory management is very often a bigger issue without a GC than with a moving GC. Time and again we see Rust or C++ programs spend 30-50% on memory management.
> Productivity is something that is dead if you are AI-heavy.
Really? Have you had AI write a good medium-sized (say 100-500 KLOC) program or maintain one over a long period of time without very close reviews? The only people I've seen who don't know about the ticking time-bomb agents leave in the codebase are the people who don't look.
> With AI, this doesn't matter anymore, for better or worse.
You may be talking about small programs. I agree that for small programs, low-level languages can offer excellent performance, and AI can be okayish, and you can get some observability you can live with, but I'm talking about large programs.
> But I think the reason Java is chosen have little to do with the reasons you've mentioned above and more with organizational preferences.
Those organisational preferences are due to a long record of delivering on the things I mentioned. Java has an exceptionally low "regret factor", i.e. people who regret choosing it five, ten, or fifteen years into a project (which is when the problems usually start).
I don't agree. If anything these newer languages have better tooling and new projects are always built from ground up to support open standards like open telemetry
Open telemetry is about how telemetry data is reported, not how it's collected. It's hard to compete with JFR on the breadth and depth of low-overhead, in production telemetry, built into the standard library and the JVM itself.
I'm not sure what enterprise-level collaboration means. In my experience, "enterprise" usually means: "Let's use tools that are 10 years behind, buggier than average, and have lots of half-baked features, none of which we need".
I'm not sure what kind of tools you mean, but unless you're looking for something that just works exactly the way EJBs do for some mysterious reasons, I don't see why you can't do most "enterprisey" things with Rust or Go. Or Python or TypeScript for that matter.
Yes and that's exactly what modern tooling is missing. Try to develop for node.js 0.2.12 on today's update of Visual Studio Code. See? No enterprise-level collaboration for ya.
Rust is too low-level for typical enterprise app where requirements changes twice a day. You end up spending time and tokens fighting with borrow checker.
> Rust is too low-level for typical enterprise app where requirements changes twice a day. You end up spending time and tokens fighting with borrow checker.
In my experience, you do not spend tokens fighting with the borrow checker anymore, newer models are smarter. But it might not be ideal for a lot of CRUD applications.
> C# is MS product, which is no-go for some folks.
This is 2026, it's not 1996 anymore. .Net works on Linux and Microsoft is as friendly towards open source and open standards as a Big Tech company can be.
If anything, it was Oracle which more recently sued another company for using a JDK alternative. And this was a lawsuit that, if accepted, could have put the entire idea of API compatibility in danger and deal a severe blow to the Open Source movement.
Anyone who is morally bothered by MS but is unfazed by this is probably just mentally stuck in the 1990s.
> Kotlin probably would be the answer.
I love Kotlin, but I'm afraid that's not the case. The conservative organizations that choose Java out of inertia, would keep choosing Java over Kotlin, even if Kotlin is a better JVM language which is facing no downside.
For anyone who doesn't need to be on the JVM or work with JVM tooling, Kotlin doesn't cut it. It doesn't have null pointer dereference problem in theory... Only it does in practice if you're using any Java API that may return null (all these bang-decorated "Platform types"). Generic type erasure can only be overcome in inline functions with reified types. And building and deploying artifacts without docker is still a mess.
I found Kotlin extremely publishing for Java shops in the past, and I've converted multiple departments totaling over hundreds of employees to use Kotlin. But that was before AI. The rationale was simple: Java is an entrenched language that leads to bloated code, slow development cycles and way too many avoidable bugs in productions. Kotlin solves some if these issues, and it's very easy to learn for a Java engineer, while still letting you keep all of your tools and libraries. And as a language (putting ecosystem aside), I find it better than either Go or Typescript, and far more ergonomic than Rust[1].
But all of these arguments die with AI. Rust is just as ergonomic as any other popular language today if you're using an agent, and the fact that an engineer spent their lifetime writing Spring Boot programs in Java you don't have time to let them learn a new stack from scratch doesn't matter anymore.
Sure, there are many companies where letting AI write the code is still not acceptable, but most of these workplaces will accept AI agents sooner than they accept Kotlin.
I feel a bit sad since I like many ideas about Kotlin (especially how amenable it is for making DSLs) but we've lost that opportunity
--
[1] Unless you have to write highly concurrent code without any data races.
> Rust is just as ergonomic as any other popular language today if you're using an agent
Have you worked on large (>500KLOC) codebases with an agent? Not only do you have to be an expert at the language, but even if you're lucky and everything is fine, Java code is likely to be particularly fast by comparison, because the agents aren't very good at manual optimisation, especially as the code grows (they're even worse than humans at that, and humans aren't great at manual optimisation of large codebases, either, which is one of the problems the JVM set out to solve; in fact, agent-written code in a low-level language gets pretty slow well below that size). Oh, and the long build times certainly don't help.
Any mainstream language can be reliable. Java is a good choice for greenfield projects when it fits the organisation’s existing stack, expertise, or the broader industry ecosystem. Just like any other language.
Banks, telcos, etc. aren’t monoliths either. They use plenty of different languages depending on the team, system, and requirements. Java isn’t inherently the choice for greenfield software just because reliability matters.
It's stable to the point of boring, and there's no shortage of people who know the language and can work with it, it's got best in class tooling, decades worth of libraries almost all very mature. Most of the language's issues are from legacy code bases coded in a style that isn't really relevant to a greenfield project.
The ecosystem has (at long last) standardized on JSpecify (https://jspecify.dev) for nullability annotations. JSpecify allows you to annotate a package or module with `@NullMarked` and your IDE and build (via ErrorProne+NullAway, typically) will check for null safety.
If you develop a library in Java and use it from Kotlin, the built-in Kotlin null-safety will recognize the JSpecify annotations on the library.
Congratulations. You've added another build tool and sprinkled your code with ugly annotations and ifs and Optional Optional.of(x).map(y) all over the place to get the same thing you'd get by moving to Kotlin.
I get it why this seems like a less drastic change, but this saddens me. Kotlin solves more issues with the type system (smart casts, reified types, immutability by default), without sacrificing readability. Unless I can see a solution in Java that makes dealing with NPEs as easier for lazy developers as ignoring them, I don't consider it a solved issue.
I don't really think about it too much, it works fine. We don't use Optionals, I'm not sure why you brought that up. I'm not a dogmatic person in this respect, rather pragmatic. I'm sure Kotlin is great, and I'd enjoy writing it, but for now, the vast majority of the finance world runs on Java, so it's what we use. I find it easy to work with, which counts for a lot.
It's a panic in Go, not an exception. In practice that's usually a whole process crash. You can catch panics and kinda use them like exceptions, but it's not conventional.
Not exactly the same solution as JSpecify, since it doesn't rely on annotations, but it's also more ergonomic.
I'm not comparing this to "null-restricted types", since that's a draft JEP that hasn't made it even into a preview feature. Go also had multiple proposals for explicit nilability in types, and while they probably have less prospect of ever seeing the light of day compared to Project Valhalla, as things currently stand, Go is in the same position as Java: They are both extremely prone to NEPs out-of-the-box and they both have external tooling that can help you avoid them.
Java null checkers have more comprehensive coverage potential compared to Go, but Go is the more ergonomic one here. You don't need a single extra annotation on your code.
Can I trust code I’ve written myself with no guarantees from the language? Maybe. Can I trust code written by dozens of other developers (and/or agents) working on the same project over multiple years? Definitely not.
Can you explain what the issue is with nullability here? Is the concern that someone's code returns null in normal circumstances but doesn't document that well, so you don't check if null? Cause if it's an error situation, one way or another some exception has to be thrown.
Most engineers do not have the ability to impose rules by fiat on all of their coworkers. It seems like you're misunderstanding the nature of working on a codebase as an IC when other developers contribute to it. If all of my coworkers don't want a lint rule I propose, I don't get to add it. If all of my other coworkers want to write code in a certain way and approve each other's MRs with code written in that way, I don't get to veto it.
Most engineers don't get to decide to use a language either. Usually someone with the clout to pick a language has the clout to set style requirements too.
They do get to decide which jobs they take. And the languages involved are one of the easiest filters. A lot easier than checking whether the code a company actually writes is any good.
Theoretically you don’t need to write AbstractFactoryProvider in Java, but looking at languages mentioned in job offers, I have a pretty good idea of which of them have a high probability of working with such code and which do not, even if all of them say they have the best code ever.
I don't disagree, but that sounds more like a response to the person asking "what's the argument for picking Java?" than one to the someone who finds "Have you tried not returning null or constructing incomplete objects?" and "Why don't you have any coding standards?" to be poor takes.
If someone's asking "why Java" or is saying nulls make it a hard no, then you'd assume that they have a choice in the first place, which generally means they also have some ability to set coding standards at the same time that they're choosing a language.
Scala technically allows you to use nulls or throw exceptions pretty much wherever (necessary for Java compatibility), but it's not an issue because people simply don't outside of super niche situations (generally some low-level thing, or a shim). Similar to `unsafe` in Rust. Or casts in all sorts of languages.
> If someone's asking "why Java" or is saying nulls make it a hard no, then you'd assume that they have a choice in the first place, which generally means they also have some ability to set coding standards at the same time that they're choosing a language.
I don't understand that logic. I sometimes ask people to explain why they think a certain policy should be implemented by the government after they state their support for it, but I don't have the ability to set government policy. I have trouble imagining you genuinely assume that any time someone asks you why something should be the way you say that you think they have the ability to change it if you convince them.
Of course you assume that; if you're talking about what a policy should be, then you work in a hypothetical world where the policy can be chosen. You don't say "but what about some other minor detail! That would require an additional policy choice, and we can't change related policies."
Like if I think my business should open an hour earlier, and you say "but the employees won't be there yet so who will open the doors!" obviously the solution is to also change the work schedule. When you have closely related policies, generally the same person/people are empowered to make both changes.
Everyone has to deal with other code that might not even be from the same org. The "check it in CI" answer isn't an excuse either. You're bolting on so much extra crap that way.
I just don't see why nullability is a problem in the first place.
I don't think I've encountered an external library that returned partially constructed objects returned nulls (at least not without a @Nullable). There are probably cases of this existing, but those types of libraries don't tend to see a lot of users.
I admit I haven't worked in Java for years, but no project I've seen at my current company (the only one I've worked at since agents have been a useful thing) is anywhere close to removing all dependencies. From what I've seen, people want to spend tokens on new things, not things that are already known to exist. Even if you can reinvent the wheel, it's not something that an employer is going to be particularly happy to subsidize.
It is really not a big deal nowadays, the problem of the same scale as having index out of bounds error (no language has good defence against this, yet it is not a catastrophe).
That's expected (the index out of bound). You have an array, and maybe it grows, you read a number from input, you don't check it against the size of the array because you want to torture the language, use it to get the element at that index and... I'm sure that there is a surprisingly number of different designs of what it should happen and a number of designed ways to ensure that it doesn't happen. But a runtime error is expected.
yes, so are the NPEs - both are runtime errors indicating a bug in the code. NPE was a major source of irritation 20 years ago, but what many people do not know is that debugging NPEs in Java is easier now - they carry more information about the source. And the culture has evolved.
> but what many people do not know is that debugging NPEs in Java is easier now - they carry more information about the source
Unfortunately, no, they don't. Not after your application has been running for a while; newer JVMs arbitrarily decide you don't need the stack trace anymore, and all you see in your logs is "NullPointerException" (unless you still have the logs from several weeks ago, just after the last JVM restart, which might still have the full stack trace). Older JVMs were better, since they always had the full stack trace; debugging NPEs was easier with them.
Unlike C it is trivial to catch a NullPointerException and confine the crash to the unit of work. And unlike C you are not talking about insanely dangerous pointers, you're just talking about an NPE.
I'll admit it's a hassle when something wasn't initialized properly and then you get a null pointer exception at some unrelated code much later. It's not always easy to debug. Catastrophic? No!
There are a lot of third party tools that can check for null safety and a lot of work is being done to make Java's initialization safer but also a little more flexible, there is
and there are all sorts of practical answers. Nulls in Java are low on my list of annoyances, way behind front end programmers who pepper my CSS files with "!important" because they don't know about precedence (though maybe they think my .clazz.clazz.clazz selector is brain dead!)
I’m not sure how long it will take, but please - can we stop saying that annotations like @IHopeThisWontBeNull is a toy for kids and, having so many years of incidents caused by those and having LLMs to write and fix the code, we can rely on language and compiler already?
You're drawing a distinction that doesn't matter in practice. If you encounter a NullPointerException incident then you either didn't annotate your code or you didn't run the tooling. (In fact before even running your CI suite, any serious IDE will tell you immediately that you've mishandled null somewhere.)
I get that some people feel like it ought to be built-in to the language rather than a separate tool... but people's personal feelings are irrelevant to the lived experience of my day-to-day work, where worrying about null is truly a thing of the past.
When building boring web applications with a sizeable team that need to run for a long time. Hiring developers is easy since there are many, there is nearly no magic and the language is quite strict and type safe so it works well with a large team.
And that "team" nowadays may also consist of many AI agents. In my experience Claude Code for example works very well with a typed, slightly boring language with lots of framework and library support. Because it doesn't compile when you get something wrong, instead of getting a vague runtime issue that Claude can't always see.
I agree with the rest, but there's definitely a lot of magic in Java. This is from both what features the languages makes available (many) and how the community uses them (often). I've had so many hard-to-debug issues in Java over the years due to reflection, annotations, and bytecode manipulation shenanigans.
And another positive point for Java: checked exceptions. It's verbose, but knowing exactly in which ways a function can fail is extremely helpful for building robust applications.
A lot of that is coding style. I’ve also seen a lot of hard-to-debug issues in Python caused by reflection, weird decorators that muck around with name-mangled symbols, and bytecode manipulation. You can even manipulate the traceback object so it’s more difficult to make sense of why the exception comes from.
It took me quite a long time to accept that the recommended unit testing library manipulates bytecode so that the exception message for `assert a == b` prints the values for both.
WRT magic, I've generally thought that was a result of frameworks - Spring, for example. In the past, my feeling was that these impose a sort of meta/configuration language that itself is not checkable at compile time, so you'd get weird runtime errors that are somewhat inexplicable. This was like... 2018 though, so perhaps things have improved.
I'd argue that checked exceptions are still worth it, even though all the problems pointed out do exist. And that's because it works to inform consumers of what a producer is doing. Haskell has the IO and Maybe monads; Java communicates the same information through IOException and other domain exceptions.
Many times I've decided to switch from one function to another, or even an entirely new library, because the checked exceptions told me that it was doing far more than I expected, and I was not comfortable introducing those new failure modes.
It's far from perfect, one still has to handle nulls and wrapped/merged exceptions, but overall I like this language feature.
>in places where it's pointless to check, like IOException
Can you explain why this is pointless? In my mind, this being a checked exception would hopefully be a hint that I should think about this failure-case and make an explicit decision whether to handle it or not. Network connection failed? Maybe I retry. Maybe I store that data somewhere else as a fall back. Isn't this similar to Go programmers needing to check if err is not nil?
I don't think I can recall a time where I routed-around-the-damage on the basis of a particular typed exception.
As soon as you consider retrying a network failure, you immediately need to start thinking about distributed systems failures, idempotency, and all that good stuff.
As soon as you start thinking about the above, it becomes immediately obvious that low-level calls should not be able to decide to re-run themselves.
I appreciate that there is a _ton_ of different experiences out there when it comes to solving problems, but I _have_ encountered exactly the case I was describing, which is what led me to my original question. Isn't the fact that it was a checked exception that led you to "consider retrying a network failure, you immediately need to start thinking about distributed systems failures, idempotency, and all that good stuff" worth it as opposed to an unchecked exception you may not realize is being thrown?
Mostly I think they are a mistake, like in ordinary application code instead of catching close to the throw you want to do a lot of
try {
...
} finally() {
...
}
to make sure things get torn down that have to be torn down and let the exception go to the top of the unit of work and probably to whatever drives the work unit. You can probably do better than logging the raw exception and moving on to the next work unit but you can do much worse. That is, you want a default "sloppy" error handling approach that's correct that you can do without thinking and avoid other kinds of "sloppy" coding encouraged by checked exception such as catching exceptions locally without doing the right thing globally.
Occasionally though I have built something really sensitive, like an authentication filter for a web site which has at least 5 ways to log in and in that I have a hierarchy of exceptions and use checked exceptions heavily to document all the ways things can go wrong and felt like "the type system really has my back here" but that is like 5% of the Java I write.
Scala's ZIO also demonstrates that they're a great idea and can be perfectly ergonomic, but you need type inference, which Java devs were resistant to for a long time (maybe still are? I remember lots of "how will I ever know what `val a = new Animal()` is???"). If you infer the exception type, they're basically invisible except for when you forget to have some place in your program to handle them, which is exactly what you want.
IMO compile-time annotation processors such as Lombok and MapStruct are far from the most magic part of Java. They're straightforward code generators. Their impacts is localized to where they get applied and you can actually see the code that's generated. They're very good for diminishing boilerplate. They're no worse than Rust's very standard #[derive(xyz)] proc macros.
Having the code being generated on the fly (instead of a one-shot) means it follows the rest of the structure it's derived from i.e. equals() and hashCode() don't risk to be forgotten when adding a field to a class (hello maddening Map<> lookup errors)
Also, yes, Lombok is _funky_ in how it works but there are "pure" alternatives like AutoBuilder and AutoValue if one cares.
> And another positive point for Java: checked exceptions. It's verbose, but knowing exactly in which ways a function can fail is extremely helpful for building robust applications.
Sorry, but no, Java has the worst of both worlds here. It has checked exceptions AND unchecked exceptions, AND errors which are like unchecked exceptions but won't get caught by a normal catch-all (you're not supposed to catch Throwable, but it's the only way to prevent some dynamically loaded plugin code ten layers deep in the stack from breaking your invariants or stopping your periodic scheduled task due to an errant NoSuchMethodError or NoClassDefFoundError).
And you can't easily use checked exceptions with Java8-style functional code, since interfaces like Function aren't generic on the exception type. Which leads to aberrations like UncheckedIOException, which exists only to make IOException usable in the functional world.
> but knowing exactly in which ways a function can fail is extremely helpful for building robust applications
I've worked on Java apps that have failed in mysterious ways that no exception could explain. Meanwhile, the overhead of having to call out certain exceptions but not others in language syntax is a bit excessive.
For example, decoding a byte array (or URL encoded form field) into a UTF-8 string means handling a theoretical UnsupportedEncodingException. What the fuck? How the hell can one have a JVM that doesn't support UTF-8? Why does my code need boilerplate that will never run because there might be some broken-ass JVM out there that that doesn't support UTF-8? How did it launch a web server, safely load all the libraries, and accept a web request, and route it to my code without blowing up? "But the encoding scheme might change..." No, it won't change. It's always going to be UTF-8. It will always be UTF-8. If it's not, let it blow up.
It works well enough with plain Ruby and plain Javascript. It ported a Rails 7, Vue 2, vuetify 2, vuex app to Rails 8 (ok, easy, I did it myself at least once), Vue 3, Vuetify 4, Pinia. I had to visually check the SPA, of course.
Java & Spring is a good choice whenever you want your application to work and be maintainable 10 years from now, without having to replace the framework and half of the libraries you used. I see few good reasons to ever use something with unstable ecosystem (like Javascript with NodeJS) over Java these days.
Stability is a good point, although I am curious where JS and Node stand there now. They're not at the level of Java or .NET by any means, but the JS ecosystem has definitely begun to slowdown over the last few years. I've used express for the server and winston for logging for years and years now and they've very stable at this point.
I guess I'm asking this as an open question: Where are we in the "move fast vs stable" spectrum with Node these days? Definitely not rock solid, but it's moving in that direction I feel.
When you are already familiar with it or work in a Java shop, there are better options if you are starting from scratch, but if you already have 50 guys that know Java it's a pretty big ask for all of them to switch.
Most organizations that use Java tend to be pretty conservative with their technology picks and nowadays with newer Java versions the only real gap with Kotlin is null-safety which is supposed to also come to Java at some point.
There is also an organization culture component most of the time, one our engineers actually proposed to use Kotlin for one of the new projects but it got rejected because "We are a Java shop"
It's a stable known stack. It's not hard to find Java developers and the AI Agents are probably pretty good at writing Java too. A Java backend will just sit there and do its job happily forever and you can bolt on whatever front-end you want. Spring Boot has been kind of the standard way to do Java web applications for probably a decade if not longer. It works fine has all the bells and whistles when you're ready for them and most Java developers who work on the web know Spring already.
As for an individual developer doing a side project, you should use Java if you haven't used it before to get exposure to it. It's a fundamental component of enterprise software and if you've never used it before take the time to learn something new.
Good question - am using for a greenfield AI startup in SF. Been a great decision so far: great ecosystem, bulletproof runtime, fantastic performance and new quality features arriving on a steady schedule. "Boring technology" at its finest.
Golang gives you none of nice features of a modern language while being about the same performance tier as Scala or Java, so there's basically no reason not to use Scala.
It's sad - I spent a good 12 years writing Scala every day and it was the ideal language for my brain. Until it wasn't - sbt got too complex for it's own good, everything became "very smart" developers over-using implicit conversions, you couldn't find a project that wasn't an opinion war on cats vs whatever. It collapsed on the weight of it's own smugness.
go and kotlin aren't it, gleam scratches the itch but I can't justify writing code that would impossible to hire for.
Every job I've has has used different languages so I don't really understand the need to find a dev for a specific language. I went from network firmware in C to banking application servers in Scala and it took like 2 weeks to ramp up. Not a big deal. Now I write lower level networking stuff again in Go, which seems like its just worse than e.g. C-with-templates (and occasional classes) style C++ so I don't really understand why people like it.
I think it used to be common to just look for smart people and assume they can run with whatever stack. Wasn't that the point of abstract algorithm questions etc. (basically an IQ test)?
>I think it used to be common to just look for smart people and assume they can run with whatever stack. Wasn't that the point of abstract algorithm questions etc. (basically an IQ test)?
Lots of companies where software isn't the focus see it as a cost center, so they'd prefer to hire lower-IQ specialists instead of higher-IQ generalists, because the latter are more expensive/have more options.
Java is almost always significantly faster than Go because the Go runtime does a poor job of exploiting large memory page, doesn't support text-on-huge-pages, and barely supports profile-guided optimization. With HotSpot you get all of this and more for free. Go is fine but Java is peak.
I ported a moderate sized java project to golang. Test suite runs order of magnitude faster now. There isn't much change in terms of the architecture. Pretty much the same algos and data structures. The whole dev tooling runs on a 16 gb mac without swapping now. I used vs code for both
IME they're both in a place where Rust is maybe ~40% faster for a decent CRUD web application server, but with go you need to write much lower level code to get there (e.g. using composable generic iterators will ruin your allocations, so it's all manual for loops). You can write idiomatic high level Scala and get the same performance. Which could be as simple as the go compiler offers no ability to force inlining and has way too low of a complexity threshold, but that basically makes reusable code unusable in high performance situations.
The whole go team's philosophy tends to also revolve around assuming their users don't know what they're doing, which is annoying. Like an inline keyword: thinking you know better than me doesn't mean I'm not going to inline it; it means I'm going to manually write it inline myself in the code, and then think the language sucks because it's tedious, error-prone, and verbose. Or they tend to mark lots of stuff private for no reason, and e.g. with TLS 1.3 they just ignore your config because they think they know better, etc.
Isn't this mostly about java cold start costs? It might be that other people are optimizing for steady-state performance, not transient startup performance.
One particular test was running for 20 minutes, doing repetitive calculations, hopefully enough to get jitted. It finishes much much faster now. I could have profiled to check what was going on but the test was simple and the dev tooling and the ram usage was a major concern for me. Also gradle upgrades were painful.
Java tooling taking up a lot of ram was a major motivation for me. I have done a lot of Scala as well. I don't think either Java or Scala in the real world beat go on performance for most cases. I don't doubt that in some cases jvm can do better but at least before Valhalla delivers all the promises, in real world, I am doubtful.
I have been a Java/Scala user almost for the majority of my career. I doubt I would pick jvm over golang going forward though. Also not having to deal with OOP is a plus.
Yes.. lol. The biggest argument now is Kotlin having nullness by default in the language. Just check around the comment section. Now java is planning to have them which will further help jvm to optimise for performance. Not sure what the next argument will be after.
Often? It's a relatively modern language with enough functional programming features to keep mid-high blub programmers happy. Yeah there's cruft; all mature languages have cruft.
Kotlin is the obvious replacement, but the tooling isn't as good and the community isn't as large. Java keeps getting better, and in ways that diverge from Kotlin - eg, virtual threads vs async/await/coloring. From the perspective of language design, I prefer Kotlin. But I keep picking Java anyway, and I don't see that changing soon.
Go is openly hostile to functional programming. Dynamic languages aren't even in the running. Rust is too low-level for line-of-business software. C# is too Microsoft. The remaining alternatives are too obscure.
java is a great language for server side projects. it is actively maintained, the biggest issues with it have JEPs, and it’s very friendly to AI authors
It's decent for backends. I'd rather use JS, but there can be performance or ecosystem reasons to use Java. They fixed a lot of the gaps it had. JS used to have a big edge in async-await while Go had n-m multithreading, but now Java has the latter.
Why should anyone use it over Java?
Ms is hostile towards its developers, it creates new versions of things, deprecates previous versions, uses confusing naming for newer versions.. etc.
Microsoft has come a long way since Satya Nadella took over in early 2014. The open-sourcing of .NET Core that same year was a huge step forward. Seeing a 'Microsoft Loves Linux' slide that year was something I did not have on my bingo card. VS Code and the GitHub acquisition demonstrated Microsoft's interest in fostering good relations with developers instead of alienating them. I do wish GitHub had stayed independent, though.
Microsoft is a business and will always put their business objectives first. In my opinion, they have a non-zero amount of evilness. I do not support them jamming Copilot into every available crevice. I still think they make dumb choices, like every imperfect organization. However, C# is a powerful and intuitive language, and for Microsoft shops that already run a lot of Windows and SQL Server it makes a lot of sense.
No shade to the JVM. I've mostly enjoyed my time in that space. I do believe the choice between Java and Kotlin, the wide variety of vendor JDK distributions and IDE fragmentation make the JVM stack a bit more difficult for newcomers to break into.
Because your employer is dick-deep in Microsoft psychosis.
I've been a .NET dev for a decade now. It's perfectly serviceable, but I wouldn't say I truly love the language anymore, but I would take it over Java any day. Entity Framework and LINQ are gifts from the Gods. I have never used an ORM that even comes remotely close.
Also, C# is big in the gaming world. I am working on a game right now, and I was not impressed with what many other languages had to offer. It seems like the kings are still C(++) and C#. Of course, Java can create games, but I would argue that is a "could vs. should" kind of decision.
Unity, Godot, Monogame, Raylib, XNA, FNA, etc. all can use or rely on C#. I have not seen Java be compatible with any of those -- except maybe Raylib? I do not know of anyone nor any games that use it though.
anecdotal evidence: I‘m working on a product in circular economy space at the moment (chemical trader). I chose Java because it just works and allows us to focus on business, no npm supply chain drama, no „how can I integrate my go microservice with a customer SOAP endpoint“ problem, time to hire under 2 months etc.
Java-the-language blows, but Kotlin does not, and Java-the-platform is on the Pareto frontier of oldest-yet-most-usable open-source ecosystems. I prefer Rust, and the gaps where it doesn't apply, C# fits my use cases better, but Kotlin/JVM is a rock solid development platform.
JavaFX is a hidden gem. I really like the programming model with its binding and scene graph and CSS.
It's not as portable as Swing, as it has some platform specific binary components to it. But it works fine on mainstream platforms. For me Swing portability is not worth giving up the FX model.
Just be aware that if you happen to bundle in the Web view component, you're basically adding WebKit to your distribution. I did this with a small project because I wanted to have a "help" screen with Markdown -> HTML. Easy, but "expensive". It simply adds a big chunk (10-20Mb) to your distribution.
(Now I have a very crude Markdown renderer for this task, which is a 100 lines code, and I'm working on a better one -- but I have yet to pull the trigger on the latest FX with its new Rich Text component, which could change everything.)
One hot tip with cross platform FX, however. Embed your fonts. The font suite is not common across the distributions, and the CSS does not honor the font fall back (i.e. if not XXX font, then YYY font), so if the runtime doesn't have your specific font, it collapses to the System font. So, embedding the fonts you use helps a lot with cross platform stability. Plenty of free fonts, I have not had a real problem with this. But it can be one of those O.o moments when you test on other platforms and encounter it the first time.
Java and C# seem to be the best ways of making code-first OpenAPI based servers.
C# LINQ also seem to be the best compromise between ORM and raw SQL queries, although I never used it myself.
I have been severely disappointed in all similar solutions for Go at least and I imagine Rust does not have something better given it has a smaller community-base.
Python and NodeJS have some very neat solutions for this stuff too, but both are "slow" dynamic languages. I personally dislike python with a passion and NodeJS stuff is extremely community-driven and therefor often unreliable. Prisma (NodeJS ORM) for example just did a major overhaul and is now pushing a completely different API.
If you are making boring REST API to SQL Database it seems like Java and C# are the best options.
Whoever works with, or chooses Java, is not doing it for the language itself, be it beautiful or not. Java has a huge ecosystem, from battle tested integrations to optimized images to build pipelines to whatever, so at the same you're buying access to all this world (yes, more than an environment). And of course transferable skills. I'm not saying Java is alone offering this, also not saying every feature is the best, but you can have them all, and even choose from different options.
Java's ecosystem is lingering since Oracle brought the language, and it's at the point where you should really look if the things you want to use are still in the state of the art, or if they felt behind every other language.
And if you are starting from scratch, whatever part of the ecosystem you use, I'm not optimist on its situation improving with time.
I use Java for hobby projects, I think it's design choices make it a nice minimalist language for "classic OOP" style: dynamic dispatch, encapsulation etc.
Nowadays a lot of code is written with mostly procedural style with some functional characteristics, I wouldn't use Java for that.
