Quarkus (Java) vs Fiber (Go): Performance Benchmark in Kubernetes

[@AntonPutra]

🔴 To support my channel, I'd like to offer Mentorship/On-the-Job Support/Consulting ([e-mail])

[@ooijaz6063]

Are you sure that both apps are using same amount of connections in pool? Connection pool often makes most of the performance diff in this kind of benchmark. Quarkus defaults to 20 concurrent connections, and pgpool to 4 or runtime.NumCPU() from what I have read. Have you check performance for more than 20 connections in a pool?

[@AntonPutra]

@@ooijaz6063 I used the defaults, but for the next tests, I'll double-check how many connections are actually opened on the PostgreSQL side.

[@111segasonic]

Perhaps you could also try helidon SE instead of quarkus. Helidon was built from the ground up by Oracle labs to use the latest java tech like virtual threads to serve requests

[@AntonPutra]

@@111segasonic thanks i'll try it out

[@Comeyd]

I’d love to see Rust thrown into the mix as well!

[@PanicAtProduction]

A benchmark must be like this. State of art. Good job!

[@AntonPutra]

❤

[@ChengPhansivang]

What is state of art mean ?

[@AntonPutra]

@@ChengPhansivang i guess something that people can relate to :)

[@avalagum7957]

Wow, this is really good. The setup (kubernetes cluster, prometheus, grafana ...) deserves another video.

[@AntonPutra]

Thanks! Just in case, the source code with all of these components is in my GitHub: github.com/antonputra/tutorials/tree/main/lessons/201/monitoring.

[@rajivkumar-ub6uj]

Hey, can you make a video on how to setup this in local? May be with k8s supplied with docker desktop if relevant?

[@AntonPutra]

@@rajivkumar-ub6uj i think so, the easiest way is just package everything as docker compose or perhaps just use local minuke cluster. i'll think about it

[@rajivkumar-ub6uj]

@@AntonPutra yes, compose is the best way for larger audience. Would appreciate if you can share the compose config for this, thanks in advance

[@AntonPutra]

@@rajivkumar-ub6uj ok

[@ДеянДелчев-ы9з]

I am go fanboy but I really like applications written in Quarkus. My first language was Java and it is mind-blowing how fast and light Quarkus feels compared to Spring

[@AntonPutra]

some people say it is slower than jvm based, I'll see if I can test it

[@lufenmartofilia5804]

You would be surprised how far spring came his way. With that being said, for long running app spring boot as none aot compiled would remain faster thanks to the jit compiler. Quarkus is really only good of you need fast startup or low ram consumption

[@awesomesuprise9141]

@@lufenmartofilia5804 good point

[@AntonPutra]

@@lufenmartofilia5804 will test, when you say long running, how long?

[@chrisfreel]

@AntonPutra long running is at least 10,000 tx before you start measuring. In the real world, weeks or months...

[@SeySvK]

Love these benchmark videos, nice work

[@AntonPutra]

thank you! :)

[@renbangbprd7236]

Please do Java Spring Boot (Native) vs Spring Boot (JDK) VS Quarkus (Native) vs Quarkus (JDK)

[@AntonPutra]

ntoed!

[@stealth-350]

And add Micronaut (Native & JDK) to this chain, plz

[@TweakMDS]

This second test scenario is absolute perfection in testing real world applications. It's easy to get excited about a performance difference of like 400% (for example) in a synthetic benchmark, but by including database, storage and (de)serializing, it gives a much more nuanced picture of how it would actually scale and perform. In this case I would say both applications performed well and comparable. I'd be interested in a bit of a deeper dive in these applications by including opentelemetry and seeing what functions might bottleneck.

[@AntonPutra]

Thanks. Well, in some tests, I used OpenTelemetry clients with this Prometheus client in both Go and Java. I'm wondering what else you would instrument besides these function calls to S3 and the database. I might include it in the following videos. example - github.com/antonputra/tutorials/blob/main/lessons/201/go-app/images.go#L50-L62

[@TweakMDS]

@@AntonPutra Must have missed that detail, very well done and thanks for the reply!

[@AntonPutra]

@@TweakMDS thanks!

[@GBXS]

But it doesn't do that much. The programs doesn't change any data. It just uploads it.

[@AntonPutra]

@@GBXS I'm thinking about adding an additional test with Kafka consumer/producer and perhaps a simple ETL pipeline. Any suggestions?

[@ninjaasmoke]

Finally! A detailed comparison that just doesn’t test the /hello-world endpoint

[@AntonPutra]

haha, thanks!

[@GabrielPozo]

Love these benchmark videos, your work is amazing!

[@AntonPutra]

❤️

[@DillPL]

Interesting comparison, BUT: - the first tests does not test the startup time itself (should be

[@AntonPutra]

I try to improve each time I create benchmarks. Next time, I will definitely use the v2 Go SDK and apply some other recommendations from your side. Thank you for taking the time to leave this feedback.

[@DillPL]

@@AntonPutra glad I could help and you haven't taken it as a personal attack or something :D I really value your videos and open source code for every video! Looking forward to seeing more of them.

[@AntonPutra]

@@DillPL thank you! i actually implemented your suggested idea in the new video and reduced the size by 6 mb (45 -> 39) :) - kzbin.info/www/bejne/a2e3hpmtms9-nNE will try other tips next as well and finally update that sdk lol

[@jorgetovar621]

This is definitely the best DevOps channel.

[@AntonPutra]

❤

[@gasha1137]

бро ты красавчик, ничего лишнего, все по делу, качество и битрейт на высоте, видосик красивый, респект!

[@AntonPutra]

spasibo❤️

[@cewa44]

From the whole video I have profited so much in percentails. You have clear so much

[@AntonPutra]

cool

[@mayboroda]

First of all, this is the best content on youtube so far. Well done. Thank you!

[@AntonPutra]

thank you! :)

[@Bourn77]

please do c# vs Java, use minimal api with AOT for c# and GraalVM or whatever AOT thing Java has.

[@AntonPutra]

ok will do soon!

[@siya.abc123]

Would love to see C# vs Go

[@krzysi3k-yt]

C# vs Go vs Java would be nice

[@AntonPutra]

any specific test scenarios? or the same

[@krzysi3k-yt]

@@AntonPutra your current test scenarios are very good so I wouldn't change anything. Regarding C# I would use LTS version (dotnet 8) which is the fastest one amongst other versions according to Microsoft.

[@AntonPutra]

@@krzysi3k-yt ok, I'll maybe do it next

[@1wsm1]

Rust - same tests

[@Serizon_]

this is so professional! I love it! please do bun vs deno v2 since deno has gotten npm compatibility , the only difference now between bun and deno (aside from being written in zig and rust) is the speed (I think , both have gotten very nice std library) please do a benchmark comparing everything!

[@RayAndrewsDev]

I really admire the effort you put into describing why you chose your testing methodology as well as the testing itself

[@henryong7788]

Seems like Java 21 was used but Virtual threads wasn't used for the Quarkus application. Wasn't that the whole point to using newer Java version with the performance improvements and non-blocking reactivity APIs?

[@AntonPutra]

yeah, i used java 21. I'll make sure to test virtual threads next time, maybe try to compare different java frameworks as well

[@henryong7788]

​@@AntonPutrahey, thanks for making this video. Just that needed to point out the code looks to be done in a older/traditional method even though Quarkus has annotations that resolves traditional blocking calls that modern programming languages like Go probably already has underlying. Great detailed video as always! Maybe I'll try this out on my local machine to test out too!

[@AntonPutra]

@@henryong7788 I'll soon be comparing Quarkus with Spring Boot, and I'll make sure to use the latest language features.

[@EricSouzarys]

Virtual Threads are not better in performance compared to fully reactive code. Quarkus fully reactive or Spring fully reactive will always beat virtual threads, both in performance and resources usage.

[@AntonPutra]

@@EricSouzarys good to know thanks

[@xelesarc1680]

Please test dotnet lastest 8 vs go thanks

[@AntonPutra]

ok, comming next

[@metaltyphoon]

@@AntonPutraensure to use Minimal APIs and compile it AOT.

[@Nick-yd3rc]

Interestingly, in your Test scenario 2, your Quarkus app is spiking in DB latency while having constant times in between, as if the Postgres client would be idling to gather the queries (or waiting on a lock?) and send them in bursts.

[@AntonPutra]

yeah, I noticed it

[@or1699]

Great video! The benchmarks were really helpful. Keep up the great work!

[@AntonPutra]

thank you! will do

[@slansky6626]

Excelent video, thank you so much! Do you think you could show this same benchmark comparing quarkus and go pushing both to its limits as you've done in your other videos?? I'm really curious about how they both compare on performance under heavy loads. My guess is quarkus would break first but I wonder how big is the difference. (I'd expect both are kinda close) Excelent work, and I'm very excited for your future videos!

[@shamilAliyev92]

Could you do the same test for Kotlin and Java ? Or Kotlin and Go. Please 🙏

[@AntonPutra]

ok let me see

[@belkocik]

​@@AntonPutra Would love see a Quarkus and Kotlin benchmarks compared to Spring Boot and Kotlin

[@AntonPutra]

@@belkocik 🫡

[@ManuelMartinez-nl5cy]

Great videos like the rest of what you do. I'm using your video sto improve my knowledge on cloud/kubernetes area.❤❤

[@AntonPutra]

thank you!❤

[@kamurashev]

It would be interesting to see what happens if you push requests to the limits and how high that limits are. Additionally for the Java it can be build to native image with spring boot as well. It sometimes not that smooth though but honestly I expect it to perform better with spring boot.

[@ooijaz6063]

Idk, native image crashes randomly and have lower performance than jited code atm. It's good only (if not crashes) for low traffic applications on serverless.

[@kamurashev]

@@ooijaz6063 I haven’t loaded my test app extensively but for me it worked ok and had better performance.

[@ooijaz6063]

It may change though with strong adoption of virtual threads in next few years and servlet api will be good again.

[@AntonPutra]

I have the same limits for both: github.com/antonputra/tutorials/blob/main/lessons/201/deploy/java-app/deployment.yaml#L27-L33, and I run them on dedicated nodes using the ESXi Hypervisor.

[@kamurashev]

@@AntonPutra I do understand, what I wanted to say is what happens if you push client requests higher and higher. The load seemed to be not that high, so the light load conditions were tested but what would happen under high load? It can be really detrimental in real world.

[@robertoaraneda6006]

thanks for sharing.. can you do it with nodejs :P?

[@AndrewGraaff-n4g]

Great video. Did you use the Reactive version of Java or the OS Thread version? If the Blocking version it would be interesting to see what would happen if you ran those on virtual threads. And what were the results of the reactive version.

[@AntonPutra]

thanks, it's been a while, but you can find a link to the source code in the description

[@AndrewGraaff-n4g]

@@AntonPutra I did. There are 2 versions and it looks like the regular hardware thread version was used. Since these workloads are all IO it would be better to use virtual threads (annotate with @RunOnVirtualThread) or the reactive version. But maybe the reactive version was used. I have always seen better performance on Quarkus than Go so these results are a bit surprising.

[@AndrewGraaff-n4g]

@@AntonPutra But your work is amazing. And I shall surely learn from it, especially the observability.

[@jordanrothschild8310]

Great video! The test seems a bit unfair to Java, as much of the time was likely spent serializing JSON, which can vary significantly based on the library used. It would be interesting to see results with a more complex application that uses intricate data structures, as Go’s garbage collector introduces pauses and latency, while Java is known for its efficiency in these scenarios. Now, on the topic of environments and the test setup, I have a few questions. Is it statistically valid to compare a test run on Kubernetes with minimal requests? For the comparison to hold up with few requests, each application's runtime environment would need to be exactly the same, which can be difficult to guarantee given the cluster load and where each pod is deployed. It might actually be easier to run the test on your local machine, where you can control the resource allocation. However, I noticed you’re using a Mac, so factors like virtualization might make the results diverge even further from what you’d see in a production environment

[@ПавелАвдеев]

I'd be interesting to compare Hotspot (various GC) vs GraalVM(Quarkus, SpringBoot)

[@AntonPutra]

ok let me see

[@terribleprogrammer]

It would be interesting to test long term throughput in this comparison.

[@AntonPutra]

@@terribleprogrammer how long? day, 2, a week?

[@terribleprogrammer]

@@AntonPutra one week would be interesting. You can also mix up jvm, graalvm and go Lang in a single video

[@AntonPutra]

@@terribleprogrammer ok, i'll see if it makes any difference and if it does i'll make something

[@vishnugovindan8550]

What about micronaut? Would love some benchmarks on this 😊

[@AntonPutra]

ok, i'll take a look, i'll get back to java soon

[@john33john33]

a good indeed comparison. only one thing wanna further look into, how do same test behave at high throughput like 500 / 1000+ req/s

[@AntonPutra]

Thanks, I may include screenshots or just improve my tests in the future.

[@ramencombo]

Why does Java's memory usage is high when it is idle? Also will it also go high when it is idle after processing requests?

[@a.nk.r7209]

How to create this setup of k8s + grafana + promethues . Please create a video of this setup

[@AntonPutra]

well i use esxi hypervisor to host my Kubernetes at home, i have some steps to reproduce it with metalb if you are interested - github.com/antonputra/kubernetes-on-premise Also to deploy monitoring stack (prometheus & grafana & cadvisor & kube-state-metrics etc) i use terraform with yaml tf - github.com/antonputra/tutorials/tree/main/lessons/201/terraform yaml - github.com/antonputra/tutorials/tree/main/lessons/201/monitoring

[@a.nk.r7209]

@@AntonPutra thanks! 🫱🏻‍🫲🏼

[@vivekchaudhary5728]

can you please do a GO vs node.js Lambda testing? with cold start time, memory usage and other metrics

[@AntonPutra]

ok i already have some lambda benchmarks in that playlist but i'll refresh it soon

[@rodhash]

14:20 seems strange Java memory decreasing once the App starts.. Java uses more memory when App is down?

[@rajumondal4283]

Lol

[@pi3ni0]

Nice job, I would like to see Test 2, but with higher RPS

[@AntonPutra]

Okay, I might just include additional screenshots under lesson '201' in my GitHub repo

[@pi3ni0]

@@AntonPutra It would be great, thank you Anton!

[@dweblinveltz5035]

Very nice video! Seems like if cost-cutting is of great concern, you'd lean towards go to keep CPU utilization down. I would love to see a similar comparison video between Java and JavaScript/Node.js.

[@AntonPutra]

thanks! noted

[@yuriimalikov9855]

Love your videos! What tool do you use for creating those amazing animations and mounting videos?

[@vladimirkashitsyn1871]

Please, compare native image of Vert.X (with java 21) and Go)

[@AntonPutra]

thanks for the suggestion, noted!

[@RiccardoPasquini]

I would also compare compile time of quarkus native and go executables....

[@AntonPutra]

ok noted

[@phyohtetpaing44]

There was a non-blocking Netty server implemented with Spring Reactive Web, which is more efficient. for databae approach use R2DBC the reactive nonblocking data repository. btw spring also support graalvm and it is not outdated.

[@AntonPutra]

ok thanks, it's not outdated just it's been around for a long time

[@yohanebergerkouokamkuisu4238]

Quarkus uses non-blocking netty

[@KhoaH11]

Nice work! The explanation around the benchmark is easy to understand and full of information there. IMHO, you should start to build your own courses on Udemy :)

[@AntonPutra]

thanks! maybe

[@kentra-io]

Very informative! How about comparing performance of java vs python stream processors in Apache Flink?

[@AntonPutra]

thanks, yes, i was thinking about spark/flink and different apis: python, java, scala, etc.

[@Sasha192_]

Please make a comparison for Java Vert.x vs Golang Fiber

[@AntonPutra]

added!

[@helloworld7796]

Okay, you got me now. I will start trying prometheus and grafana. The question I have is which tools do you use for load testing? You are using word "client" for this. I assume you use some kind of tools, like jmeter, k6 or?

[@marcwinner567]

Love these benchmarks! 🎉

[@AntonPutra]

thanks! i try to add some extra

[@Nephtys1]

Can someone explain the extreme drop in memory usage for Java here? Under Hotspot JIT I would assume something similar, but this is running on SubstrateVM instead of JVM. Sadly I have little experience with Native Image and Substrate, so an explanation eludes me. What is happening here with memory usage?

[@AntonPutra]

I'm not an expert in Java, and I hope to get feedback from someone who is, but it looks like it optimizes for the load that is given to the application.

[@EricSouzarys]

probably because of garbage collections (graalvm stills have a simple GC). The GC learns what objects need to be cycle e and what does not need. Missing JIT actually affects CPU usage. You can easily test this by running a benchmark against native code and JVM. You will see that under high load JVM version uses less CPU

[@AntonPutra]

@@EricSouzarys i'll be testing quarkus vs jvm spring boot soon, any suggestions?

[@EricSouzarys]

@@AntonPutra I think that you Just need to be careful to not compare orange and apples. I think you can compare these combinations if the tests are going to be applied to an I/O bound app: 1. Quarkus Blocking vs Spring Blocking 2. Quarkus fully reactive vs Spring Fully reactive (with webflux) 3. Quarkus with virtual threads vs Spring with virtual Threads. An extra combination could be Quarkus Fully Reactive vs Spring with Virtual Threads as virtual threads with Spring is more used than with quarkus. A comparison between reactive quarkus against Spring (without virtual threads) would not be fair

[@AntonPutra]

@@EricSouzarys ok noted!

[@pauluslestyo7646]

It's great if you can benchmark framework from bun runtime like Hono and ElysiaJS

[@AntonPutra]

ok noted!

[@ionutale1950]

nice comprarison, this could work great on a batch. how is it going to compare on an app, that has peaks during a specific time of the day?

[@AntonPutra]

Thanks! There is a very small difference in terms of scalability; both are small with a fast startup time. I think Go is a little more efficient, so potentially you would need fewer compute resources.

[@ionutale1950]

​@@AntonPutra the way java is using memory with GraalVM is very smart, is like observing the needs, then optimise the RAM needs. This could suggest that we could provision the JAVA container with a smaller POD in term of RAM. My concern is: how well does java handle random peaks? if we have 200 req/s, than right after the RAM stabilises suddenly we get 500 req/s, how well does JAVA handle that peak? is java going to panic and ask for wayyyy more memory than it actually needs? if this is the case, than the JAVA app may actually crash for insuficient container memory. Does it make any sense, what i've just said?

[@AntonPutra]

@@ionutale1950 yes, it does. i'll try to configure the client next time to simulate such spikes when I compare spring boot with quarkus

[@harshwardhanparmar8258]

Amazing video, great job !!

[@AntonPutra]

thank you!

[@alexanderv5975]

Hi. Nice video indeed. Can you explain why Java uses significantly less memory under load then in idle run?

[@BroddeB]

I guess the latency peaks in the database graph is caused by the garbage collection overhead. Is golangs garbage collection implementation that much better? Is the p90 statistics hiding some latency spikes?

[@AntonPutra]

yes, actually, there is a huge difference between p90 and p99

[@bibahbibah5108]

i wona see spring boot native image vs Quarkus vs go spring native is framework like Quarkus so it's nice to compare this 2 framework

[@AntonPutra]

ok noted!

[@vasilekx8]

Please compare envoy with nginx, traffic, caddy

[@AntonPutra]

ok will do caddy soon.. Nginx vs. Envoy performance benchmark - kzbin.info/www/bejne/ZoKcemCuYpKhppY Apache vs. Nginx performance benchmark - kzbin.info/www/bejne/fKmbkpmMj69_mpY Traefik vs. Nginx performance benchmark - kzbin.info/www/bejne/mJjGl3iNlL6bbac

[@furylao8107]

really nice approach to monitoring performance. can you make a similar video but with java profiling tool to detect which specific part of the code must be reworked?

[@GreenVanGeek]

Nice video. One comment. Scale up/down is increase or decrease the machine resources like CPU and memory. Scale in/out y horizontal scaling ;)

[@mantovani96]

Loved the video, subscribed!

[@AntonPutra]

thanks!!

[@nabeelmemon6852]

Interesting. These tests could be extended to compare Hotspot VM, Generational ZGC and a few other switches. Can you make a video of your entire testing setup (focusing on docker, kubernetes, prometheus and grafana) from scratch? I think it's totally worth it.

[@bernhardbaumgartner4702]

What’s the explanation for the memory profile of Quarkus, can someone explain this?

[@AntonPutra]

i'll run some more tests in near future

[@bernhardbaumgartner4702]

I’m just wondering why the memory usage goes up and up and up at the beginning, and at some point (reaching a threshold or something?) something like an aggressive GC seems to kick in never letting memory usage go up again.

[@malikmalik-zx1wq]

can you tell me how to query promql to display the memory usage graph?

[@korbendallasmultipass1524]

Would be good to see a native build test with GraalVM in comparison. Furthermore can Quarkus use Mutiny as Reactive Framework - maybe this would bring the two closer together as well.

[@AntonPutra]

ok noted!

[@Kessra]

Small improvement suggestion: In Java you could use a record instead of a class. This shouldn't have a big impact on the test results but at least spares you a bit of typing. It would have been great to include a base Java and a Spring/Spring Boot comparison deployed into a java21 image container here as well just to see how much of an impact Quarkus and the native container optimization really yields. So far I couldn't convince anyone at our company to try out Quarkus. Just a question out of interest: Are you going to create a benchmark framework where similar tasks are done by various language implementations and then release your findings to the public? I just stumbled across an other video and then this one was recommended to me, and to me it looks like your videos basically doing that but just with a smaller and more comprehensible scope. So a combination of runtime analysis of different languages for various tasks would definitely be helpful, I guess

[@AntonPutra]

thanks, yes i'll get to Java soon and I'll try to improve a few things

[@MovinduLochanaWijethunge]

@@AntonPutra Can you try using both Spring Boot Native and Quarkus to see how much of a performance difference they have

[@AntonPutra]

@@MovinduLochanaWijethunge yes will do

[@alienmars2442]

If those java containers are converted into graalvm native code, I wonder what the comparation will be ?

[@ilyanemtsev2790]

Can you test Spring Boot vs Spring Boot WebFlux

[@AntonPutra]

ok noted!

[@Virus00000000000001]

Could you try GraalVM next?

[@AntonPutra]

yes soon

[@Jollyrogger805]

I work on both Java and go, your results are similar to my observations. Java consumes memory due to too much of autoconfigurations which involves hell lot of classes + some of jdk had garbage collection issue but if you develop an enterprise ready application in go with distributed tracing, logging, metrics, database writes heavy operation etc, their performance is almost equivalent. I had to manually write all those functionalities in go Lang due to lack of autoconfiguration and libraries

[@nojerome497]

Very good point. Java frameworks like Quarkus are doing a lot to make large scale application development easier. All of that stuff it's doing will affect runtime performance.

[@larryliang6748]

How much memory was allocated to each program? the vidoe focused on showing the difference but I wanted to know say is a 25% usage of what. thx

[@AntonPutra]

256Mi - github.com/antonputra/tutorials/blob/main/lessons/201/deploy/java-app/deployment.yaml#L32

[@richarmunicosamaniego8216]

and what will happend with Quarkus vs SpringBoot

[@AntonPutra]

interesting, i'll test it soon

[@LawZist]

Great Benchmark! can you share the promQL for the metrics? is it some plugin or you wrote it by yourself? thanks

[@AntonPutra]

thanks! it's just open source and i actually have dedicated youtube tutorials how to measure, cpu/memory/vpc etc.. here is a dashboard and promql queries for this specific video - github.com/antonputra/tutorials/blob/main/lessons/201/dashboard.json java metrics - github.com/antonputra/tutorials/blob/main/lessons/201/java-app/src/main/java/com/antonputra/ImageResource.java#L51-L59 golang metrics - github.com/antonputra/tutorials/blob/main/lessons/201/go-app/metrics.go#L13-L27

[@LawZist]

@@AntonPutra is there any reason to prefer summary over histogram? And can you please share the link for your measure tutorials? Thanks a lot!

[@AntonPutra]

@@LawZist use summary in edge cases when you have a single instance of the app and you can only scale vertically, cause it's not possible to aggregate them over multiple instances, for example to get p90 percentile for 5 replicas of your app. With summary prometheus compute p90 on the client itself. Use histogram in all other cases kzbin.info/www/bejne/jYalm5-Ar65ll5I kzbin.info/www/bejne/jJupd619e96Jors kzbin.info/www/bejne/mn7GkmegfcaZqpo kzbin.info/www/bejne/nJfCiXujbpuDgbM

[@LawZist]

@@AntonPutra thanks!!

[@陳秉寬-t7y]

The sql latency difference might be due to the use of prepared statement

[@AntonPutra]

maybe, but go postgres driver does it by default and do not recommend explicitly "prepare" statements before execution.

[@alvinxyz7419]

this is very neat, i love it

[@AntonPutra]

thank you!

[@muray82]

It would be good to change a bit what the application is doing. In our company we have a piece of code that is meant to validate if we don't have any delays in network stack. To do so we tell the app to generate random 1000 bytes and sent that to client. With that nothing is cached.

[@ugurata]

Java runtimes were historically designed to consume the resources of the whole VM so may be you can compare a Java app running on a JVM (not a native image but a hotspot JVM) on a VM with 4 cores and 4 GB RAM vs a go app running on Kubernetes using that same VM

[@r1nlx0]

Is this using graalvm oracle or graalvm community edition ? very interest on comparing graalvm oracle AOT & JVM based vs golang

[@AntonPutra]

it should be the community version. i'll make some more java content in the near future.

[@awesomesuprise9141]

Wonderful content Anton!

[@AntonPutra]

thank you!

[@madmasontv7254]

Thanks for you video! I really like it. Could you do the same tests for Spring vs Quarkus?

[@AntonPutra]

thanks, will do, but first rust vs go

[@havefun599]

Like always you rock, can you make a video about database architecture for production like MySql Replication Group etc, Thank you

[@AntonPutra]

thank you! let me see

[@whiletrue1-wb6xf]

Great work ! What about C++ vs GO ?

[@AntonPutra]

will do! :) any specific frameworks on c++?

[@eugehacks]

@@AntonPutra drogon framework is very very fast and well written

[@ZzooD]

It would be interesting to see a test to failure, who and under what load will start throttling

[@AntonPutra]

yes will do with improved java next time

[@kawin-vir]

Would be nice to see Go (Fiber) vs Bun (Elysia)

[@AntonPutra]

ok noted!

[@germandavid2520]

Would be cool to see in a future video the framework web for Kotlin called Ktor.

[@AntonPutra]

noted!

[@helloworld7796]

I do think you should do some kind of load testing on the cheap 5$ instances. For example how many requests these cheap vps can handle before they crash, using golang, rust, php etc.

[@Ayush-lj6pq]

Please make a tutorial on Golang.

[@AntonPutra]

i have couple... How to Monitor/Instrument Golang with Prometheus (Counter - Gauge - Histogram - Summary) - kzbin.info/www/bejne/jYalm5-Ar65ll5I OpenTelemetry Golang Tutorial (Tracing in Grafana & Kubernetes & Tempo) - kzbin.info/www/bejne/kHqxaHtmZdqfh9k

[@ChristopheDCPM]

what does Java needs to have request coming in to lower its memory consumption ?

[@AntonPutra]

i think memory plays an insignificant role in these tests

[@sarabwt]

It would be interesting if you compare go vs java non native, as non native should have better performance than native. You compile java to native only if you are building a CLI or a lambda, when you need fast startup.

[@AntonPutra]

ok noted!

[@dessavio]

I'd like to see how these both perform in multithreading and concurrency scenarios.

[@AntonPutra]

can you suggest any use cases?

[@dessavio]

@@AntonPutra Perhaps an ETL pipeline or batch processing. Ingest a large dataset, split it into chunks then process each in separate threads. Store the results into a database.

[@dfghgfhb]

Link for the prevoius java spring boot video?

[@AntonPutra]

It’s a very old one. I’ll make an updated video soon.

[@volshebniyfonar]

Гуд ынглиш, май бразер!

[@HeyItsSahilSoni]

Thia is all good, checking how well it performs, but if its not throttling, anything is fine as long as client latency is not out of whack. I think some stress testing will also give good comparision, like you did with node and go

[@AntonPutra]

'll come back to java soon with improved benchmarks

[@bonk1463]

hey good test! can you test with go-chi instead of Fiber? go-chi is more optimized in terms of memory usage so that might explains why Java was using less memory in that first test. Overall, good video! Keep it up

[@AntonPutra]

Thank you! I used Chi for one of my projects, but I think memory usage doesn’t play a major role in the user experience, such as client latency etc..

[@yashshinde8185]

How to get this bench mark dashboard to check the memory, etc. performance.

[@AntonPutra]

I haven't published it yet, I may consider doing so in the future, but the Grafana dashboards themselves are in the repo.

[@Mrhennayo]

Java wise it's normal I didn't check your code but I assume that you used blocking request which in turn adds more over head and drops The cpu usage is divided between jvm + code + gc Memory java allocates the memory it needs from the get go and keeps increasing until it hits the headspace limits I'm pretty sure that maybe go can be a bit faster but we can ultimately optimize the application to handle more requests and minimize the drops by using reactor But before concluding I'm not saying that java or go or even delphi is better, constraints defines the application and vice-versa

[@AntonPutra]

I want to test the Java Kafka Streams API, maybe with Go, and perhaps build a simple ETL pipeline. What do you think?

[@Mrhennayo]

@@AntonPutra that's sounds great, I created a dummy project for that if you wanna play with

[@AntonPutra]

@@Mrhennayo thanks

[@yashumittal]

Please create a benchmark performance test for Deno 2.0?

[@AntonPutra]

yes in about a week

[@gabrielmartinez2455]

C# vs Go would be amazing to see. Maybe add to test 2 some simple reads from the database, and maybe add test 3 with some simple data structure or general purpose calculations to see how well each language performs. Amazing content. I am currently writing a high performance C# application for the government with .Net 8 and it is incredibly fast. I wonder if .net 8 has been improved so much that might even beat Java at this point.

[@AntonPutra]

Can you elaborate on using simple data structures or general-purpose calculations to evaluate how well each language performs? I don't really want to run fibonacci anymore lol

[@gabrielmartinez2455]

@@AntonPutra You can try to implement 3 different types of algorithms (In addition to the 2 tests you already did in your previous video). 1- Searching Algorithms (linear search) - ex: Create a List of 1 million objects (person: {Id, Name} - Id: must be unique integer 1 to 1,000,000. Name: generate random string. Populate your list with 1 objects (Person). Test: Generate a random Int value from 1 to 1million and find the Person object (by ID) using the random generated Int, and get the Name, then find the object in the list (by Name) compare and validate both ID match 2- Sorting Algorithms (sort the entire 1 million object (person) by name. 3 - File I/O Operations - generate random Int value from 1 to 1 million, find the Person in the List, write the Person's name to the first line in a file, if file already contains a line replace with the new name. Leverage ChatGPT to create the code for you in both languages. Just some ideas, lol

[@AntonPutra]

@@gabrielmartinez2455 thanks! i'll try it

[@KangoV]

Try Micronaut with its ahead of time compiled JSON databinding (Micronaut Serialisation).

[@AntonPutra]

ok, will try

[@VuLinhAssassin]

Can you do with Java 21 using virtual thread vs go coroutine?

[@AntonPutra]

i'll probably go with 22, i have something in mind

[@alche8411]

Great job! But a few comments: Spring supports building native images as well, and they have maven/gradle plugins and a dedicated project Spring Native for this case. Actually, we are using it in production and building most of the Spring apps in native images. Summary: GO is faster, then JVM based stuff, well no surprise here :) In general, Quarkus doesn't give anything interesting compared to Spring, it's just a bit more modern and doesn't have much legacy stuff. What might be interesting to look at in this regard is Micronaout, because it does a fundamentally different Framework (compile-time and supports native images out of the box in comparison with runtime Spring with additional projects and layers for native support). Most likely Micronaout will show similar to GO numbers.

[@AntonPutra]

thank you for your feedback. i'll get back to the java world soon, maybe next week, and make a few improvements

[@archie400]

Check java (helidon) with go (whatever framework)

[@AntonPutra]

ok will do java soon

[@humanardaki7911]

"There are no solutions. There are only trade-offs" Thomas Sowell servers are cheaper than developer time

[@AntonPutra]

true

[@andreipushkin_globant]

Not always true. Paying for each CPU cycle in the cloud you can easily get out of budget on scale. That is why optimization and algorithm knowledge is valuable again - it helps to save money.