Hi Jan, Here is a blog post related to this topic: https://sematext.com/blog/solr-vs-elasticsearch-differences/ <https://sematext.com/blog/solr-vs-elasticsearch-differences/> It also contains links to other resources that might help you make a decision.
HTH, Emir -- Monitoring - Log Management - Alerting - Anomaly Detection Solr & Elasticsearch Consulting Support Training - http://sematext.com/ > On 15 Jan 2020, at 05:02, Dc Tech <dctech1...@gmail.com> 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. > > 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 !!
