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Comment by vosper | Hacker News Reader

Yeah. There's a lot that Elasticsearch can do. There are libraries and applications that can do bits of what ES can do, but no-one I'm aware of (and I watch this space) is even slightly close to building a genuine replacement (I'm not counting the AWS fork, for obvious reasons)

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How much sense does it make for another product to try to be even slightly close to elasticsearch?

My experience with ES has been somewhat mixed, exactly because them trying to do everything at the same time and a lot of the specific things we needed being under documented and involving much more try and error than should be necessary.

I for one welcome more focused products, when the need again arises for something in this space.

I see search engine space similar to the relational database space… more features is really a good thing it helps you answer more questions about your data … just my 2 cents

Well, I suppose anything could be a genuine replacement depending on how many of the features of elasticsearch the user actually needs/uses.

However ... unfortunately, you can't just drop features from ES (or most software really) to make it lightweight.

Java already does this AFAIK. If you use a GC that supports class unloading (all the new ones do).

Unused classes can be unloaded from RAM and it's like they don't exist. The executable is still huge but lower memory and CPU cache footprint.

For a lot of use cases, you can.

Where would you say Solr falls short? In terms of search - it's definitely the case that ES has expanded beyond that (metrics, apm...)

I feel ES has been trying really hard to walk away from the features Solr is good at. While ES still supports multiple languages and custom tokenization chains and even custom pre-processing chains (somewhat equivalent to Solr's UpdateRequestProcessors), I felt that they were very deeply buried in the configuration, when I look at ES a year ago.

ES is truly focusing on metrics and things and does have some features to make those use cases easier that Solr would probably need a lot of configuration/customization for.

So, Solr is about search. ES is about a specific set of use cases that rely very heavily on search.

And Lucidworks Fusion (commercial alternative to ES) is about big data and ML and full multi-tool pipeline on top of Solr.

Elastic makes the bulk of their money from log search. Developer productivity tools like Splunk as main competitor.

So that’s where they’ve invested a lot in tooling and visualization.

ES wins hands down in search in my experience because the companies that were doing search stuff "before it was cool" were mostly running stuff like Autonomy DRE which work well but are expensive and proprietary.

There is a huge market just by going after that kind of customers.

They both use Doug Cutting’s lucene under the hood

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