From what I've seen of Groovy and Grails, its biggest hurdle is adoption. Why else would anyone resist using a language that improves on Java and a framework based on Rails?

Views: 104

Replies to This Discussion

Robert Dempsey said:
What I am looking for is performance comparisons of Groovy/Grails with other frameworks combined with Java such as Spring.

Hello Robert, Have you explored Scala programming? It gives you the short and flexibility of Groovy like expressiveness, but yet has good performance as close as to Java itself! Scala is static typed instead of dynamic though. Check out other post I made few days ago under Other JVM Group on this site see if you like it.
-Z
What needs to be performant and why? Things like Twitter are built on a notoriously slow platform (ie, Ruby on Rails) but it's plenty fast enough.

Grails is obviously slower than Spring MVC since it's built on old versions of Spring MVC and Spring WebFlow. Does it matter? For the vast majority of web sites the answer is trivially simple: No.

Scala is faster and slower than Java depending on what you're doing. Groovy is slower than both, but who cares? It's more than fast enough for what it's used for.

If you really need speed, write in assembly code. If you think that's not reasonable, then ask yourself why you're willing to sacrifice that speed to be able to write in Java. Then apply the same reasoning to why you would program in something like Grails.

Note that I'm not saying that you should use Grails, just that looking at performance without solid reasons *why* is well beyond foolish.
There are some performance issues (For example I have been told my IDE friendly specific typing can cause issues) that make Scala/Java better for some high volume projects. However, for simplicity and readability groovy is a better way to develop, IMHO

Jackie
To answer adoption - Grails is becoming more and more mainstream. Sky.com, Wired, and Walmart (specifically mp3.walmart.com) are some notable sites using Grails.

In benchmarking, yes, Grails is slower. But improvements are being made, both to Groovy and Grails itself.

And benchmarks are generally useless in the real world. Every application is different. Bad code, poor database design, poor technology choices, etc are going to have a far greater impact then the language used.

Where performance is an issue, you can always use Java (or Scala). In fact, much of the Grails framework is in Java, not Groovy. It all comes down to using the right tool for the job.

Also - in the age of distributed computing, I need to ask who cares if there is a 20-30% performance penalty. What does it matter if you need to spool up another VM or two in the cloud?

RSS

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

Presentation: How to Unlock Insights and Enable Discovery Within Petabytes of Autonomous Driving Data

Kyra Mozley discusses the evolution of autonomous vehicle perception, moving beyond expensive manual labeling to an embedding-first architecture. She explains how to leverage foundation models like CLIP and SAM for auto-labeling, RAG-inspired search, and few-shot adapters. This talk provides engineering leaders a blueprint for building modular, scalable vision systems that thrive on edge cases.

By Kyra Mozley

Article Series - AI Assisted Development: Real World Patterns, Pitfalls, and Production Readiness

In this series, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline. As AI transitions from proof of concept to production, teams are discovering that the challenge extends beyond model performance to include architecture, process, and accountability. This transition is redefining what constitutes good software engineering.

By Arthur Casals

How CyberArk Protects AI Agents with Instruction Detectors and History-Aware Validation

To prevent agents from obeying malicious instructions hidden in external data, all text entering an agent's context must be treated as untrusted, says Niv Rabin, principal software architect at AI-security firm CyberArk. His team developed an approach based on instruction detection and history-aware validation to protect against both malicious input data and context-history poisoning.

By Sergio De Simone

Anthropic announces Claude CoWork

Introducing Claude Cowork: Anthropic's groundbreaking AI agent revolutionizing file management on macOS. With advanced automation capabilities, it enhances document processing, organizes files, and executes multi-step workflows. Users must be cautious of backup needs due to recent issues. Explore its potential for efficient office solutions while ensuring data integrity.

By Andrew Hoblitzell

Tracking and Controlling Data Flows at Scale in GenAI: Meta’s Privacy-Aware Infrastructure

Meta has revealed how it scales its Privacy-Aware Infrastructure (PAI) to support generative AI development while enforcing privacy across complex data flows. Using large-scale lineage tracking, PrivacyLib instrumentation, and runtime policy controls, the system enables consistent privacy enforcement for AI workloads like Meta AI glasses without introducing manual bottlenecks.

By Leela Kumili

© 2026   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service