Thank you Jan and Charlie. I should say that in terms of posting to the community regarding Elastic vs Solr - this is probably the most civil and helpful community that I have been a part of - and your answers have only reinforced that notion !!
Thank you for your responses. I am glad to hear that both can do most of it, which was my gut feeling as well. Charlie, to your point - the team probably feels that Elastic is easier to get started with hence the preference, as well as the hosting options (with the caveats you noted). Agree with you completely that tech is not the real issue. Jan, agree with the points you made on team skills. On our previous proprietary engine - that was in fact the biggest issue - the engine was powerful enough and had good references. However, we were not able to exploit it to good effect. Thank you again. > > On Jan 15, 2020, at 5:10 AM, Jan Høydahl <jan....@cominvent.com> wrote: > > Hi, > > Choosing the solr community mailing list to ask advice for whether to choose > ES - you already know what to expect, not? > More often than not the choice comes down to policy, standardization, what > skills you have in the house etc rather than ticking off feature checkboxes. > Sometimes company values also may drive a choice, i.e. Solr is 100% Apache > and not open core, which may matter if you plan to get involved in the > community, and contribute features or patches. > > However, if I were in your shoes as architect to evaluate tech stack, and > there was not a clear choice based on the above, I’d do what projects > normally do, to ask yourself what you really need from the engine. Maybe you > have some features in your requirement list that makes one a much better > choice over the other. Or maybe after that exercise you are still wondering > what to choose, in which case you just follow your gut feeling and make a > choice :) > > Jan > >> 15. jan. 2020 kl. 10:07 skrev Charlie Hull <char...@flax.co.uk>: >> >>> On 15/01/2020 04:02, Dc Tech wrote: >>> I am SOLR fant and had implemented it in our company over 10 years ago. >>> I moved away from that role and the new search team in the meanwhile >>> implemented a proprietary (and expensive) nosql style search engine. That >>> the project did not go well, and now I am back to project and reviewing the >>> technology stack. >>> >>> Some of the team think that ElasticSearch could be a good option, >>> especially since we can easily get hosted versions with AWS where we have >>> all the contractual stuff sorted out. >> You can, but you should be aware that: >> 1. Amazon's hosted Elasticsearch isn't great, often lags behind the current >> version, doesn't allow plugins etc. >> 2. Amazon and Elastic are currently engaged in legal battles over who is >> the most open sourcey,who allegedly copied code that was 'open' but >> commercially licensed, who would like to capture the hosted search >> market...not sure how this will pan out (Google for details) >> 3. You can also buy fully hosted Solr from several places. >>> Whle SOLR definitely seems more advanced (LTR, streaming expressions, >>> graph, and all the knobs and dials for relevancy tuning), Elastic may be >>> sufficient for our needs. It does not seem to have LTR out of the box but >>> the relevancy tuning knobs and dials seem to be similar to what SOLR has. >> Yes, they're basically the same under the hood (unsurprising as they're both >> based on Lucene). If you need LTR there's an ES plugin for that (disclaimer, >> my new employer built and maintains it: >> https://github.com/o19s/elasticsearch-learning-to-rank). I've lost track of >> the amount of times I've been asked 'Elasticsearch or Solr, which should I >> choose?' and my current thoughts are: >> >> 1. Don't switch from one to the other for the sake of it. Switching search >> engines rarely addresses underlying issues (content quality, team skills, >> relevance tuning methodology) >> 2. Elasticsearch is easier to get started with, but at some point you'll >> need to learn how it all works >> 3. Solr is harder to get started with, but you'll know more about how it all >> works earlier >> 4. Both can be used for most search projects, most features are the same, >> both can scale. >> 5. Lots of Elasticsearch projects (and developers) are focused on logs, >> which is often not really a 'search' project. >> >>> >>> The corpus size is not a challenge - we have about one million document, >>> of which about 1/2 have full text, while the test are simpler (i.e. company >>> directory etc.). >>> The query volumes are also quite low (max 5/second at peak). >>> We have implemented the content ingestion and processing pipelines already >>> in python and SPARK, so most of the data will be pushed in using APIs. >>> >>> I would really appreciate any guidance from the community !! >>> >> Sounds like a pretty small setup to be honest, but as ever the devil is in >> the details. >> >> Cheers >> >> Charlie >> >> -- >> Charlie Hull >> Flax - Open Source Enterprise Search (now part of OpenSourceConnections) >> >> tel/fax: +44 (0)8700 118334 >> mobile: +44 (0)7767 825828 >> web: www.o19.com >> >
