Hacker News Reader

Comment by XPherior | Hacker News Reader

Hello, Michael Drogalis - the author here.

I'm also not a Spark user, but I have used Storm:

- Storm is significantly more mature and performant the moment.

- Storm has a better cross-language story in terms of bolt functions.

- Pretty much everything in Onyx is much more open ended. This applies to deployment, program structure, and workflow creation - and is mostly an artifact of how aggressively Onyx uses data structures.

- Onyx has a far better reach across languages in terms of its information model.

- Onyx will be adopting a tweaked version of Storm's message model next release to get on the same level of performance and reliability. We're dropping the HornetQ dependency.

- Onyx is born out of years of frustration of direct usage of Storm and Hadoop.

View on HN

As someone who has been using Storm, this looks very interesting. What I particularly like are the clean, well thought-out ideas. Also, easily reconfigurable (at runtime) topologies are something we'd be interested in. I will definitely take a very close look at Onyx.

Performance is important: in our case, decreasing it significantly below Storm's level would not be acceptable.

Also, I watched the Strange Loop presentation and the tree model looks limiting to me: I have topologies where I need to merge information from two streams (but perhaps I haven't understood the Onyx model yet).

Performance - wait until the 0.6.0 release. We'll be caught up with Storm by then.

The tree model is being removed in 0.6.0 in favor of a vector of vectors (DAG), which allows multiple inputs. See https://github.com/MichaelDrogalis/onyx/blob/0.5.x/doc/user-... The tree model wasn't one of my better ideas.

Edit: to be clear, you can do stream joins right now in 0.5.3 with the DAG model.

Hi Michael, thanks for your work creating Onyx - it looks really cool.

I can infer two of your frustrations with Storm from the above post: that Storm was too closed, and it's information model didn't span across languages very well. If you have the time, could you elaborate on these pain points, and any others that you found?

I'll paraphrase a few snippets from my own documentation to answer these questions. Happy to comment more if needed.

Information models are often superior to APIs, and almost always better than DSLs. The hyper-flexibility of a data structure literal allows Onyx workflows and catalogs to be constructed at a distance, meaning on another machine, in a different language, by another program, etc. Contrast this to Storm. Topologies are written with functions, macros, and objects. These things are specific to a programming language, and make it hard to work at a distance - specifically in the browser. JavaScript is the ultimate place to be when creating specifications.

Further, the information model for an Onyx workflow has the distinct advantage that it's possible to compile other workflows (perhaps a datalog) into the workflow that Onyx understands.

See https://github.com/MichaelDrogalis/onyx/blob/0.5.x/doc/user-... for a continued explanation of why Onyx is more of an "open" concept.

Michael, can you explain this more? "[Storm] Topologies are written with functions, macros, and objects. These things are specific to a programming language, and make it hard to work at a distance -- specifically in the browser. JavaScript is the ultimate place to be when creating specifications."

I don't really get it. Storm Topologies are built in Java or Clojure using a builder interface, but the data structures for topologies themselves are actually DAGs that serialize using Thrift. It's true that this is a bit heavy-weight compared to something like JSON or EDN, but offering an alternative is a discussion in the community right now. What would your ideal representation of topologies be, actually?

I wasn't aware that they're Thrift serializable - that's cool, and offers roughly what Onyx does in terms of its workflow representation.

Onyx goes a little further though in terms of its catalog. I wanted more of the computation to be pulled out into a data structure. That includes runtime parameters, flow, performance tuning knobs, and grouping functions. All of these things are represented as data in Onyx. It's a little harder, at least in my experience, to do these things in Storm.

Reply on news.ycombinator.com