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. 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. 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 !!
