I'm sitting in Elasticsearch training right now (during a caffeine break). These are some really great guys that know their stuff, and they're committed to contributing back to the OSS version everything that makes sense. They contribute a ton of code back to Lucene and employ a lot of the brightest minds in this space.<p>On the product side, I'm sitting here being amazed at some of the problems they've solved very elegantly. Elasticsearch has a bright future.
If people are curious as to why VCs are interested in open-source businesses:<p><a href="http://indexventures.com/news-room/blog/a-perfect-storm-now-is-the-time-for-multibillion-dollar-open-source-companies" rel="nofollow">http://indexventures.com/news-room/blog/a-perfect-storm-now-...</a>
We love Elasticsearch. It's fast and accurate for huge amounts of data, super easy to scale, and incredibly easy to get started. That cash can only make the product better. Good for them!
Hopefully this means that the documentation gets some help, especially some of the official libraries. So far working with ES has been a mixed bag… seems good in theory but I've had a hard time getting over the learning curve.
Elasticsearch is great. I have spent the last 6 months working on a project using it as the primary search technology, it has been nothing but great. I have not had any training and tried to figure it out through the online docs (which in the last overhaul have gotten much better) so forgive me if any of what I'm about to say is wrong, or better yet please correct me so I can learn :)<p>here's the things I noticed when using it:
- Since it's schemaless by default it will guess the data type of a document based on the first value it sees, as far as I'm aware you're not able to change a data type later on, so I found it best to create a schema (aka mapping) being explicit about the fields data types up front. I think explicit is better anyway (Zen of python ;) )<p>- It's blazingly fast. Like crazy quick.<p>- Use the geo data type if you're going to be doing radius queries. I've got 50M documents in the index and it queries insanely fast. It's been just as fast as PostGIS (which I also love)<p>- Use this as the GUI: <a href="http://mobz.github.io/elasticsearch-head/" rel="nofollow">http://mobz.github.io/elasticsearch-head/</a><p>- Do some proper research on filtering before you start, start here: <a href="http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/analysis-snowball-tokenfilter.html" rel="nofollow">http://www.elasticsearch.org/guide/en/elasticsearch/referenc...</a><p>the correctly configured snowball filter will make sure things like "rückwärts" will match "ruckwarts",
I have been prototyping with Elasticsearch for the last couple of months. I have nothing but great things to say about the software and documentation. Several other partner teams have taken notice of my work and will likely incorporate the software as well. Very exciting!
Awesome! I make heavy use of elasticsearch and am very happy with the performance.<p>It's typically the rest of the pipeline now that causes most of the latency whereas search used to be the bulk of the duration of a request.<p>It has also spurred other entities to improve their search performance :)
I saw these folks at gluecon. Haven't looked at a ton of dashboard solutions, but I found Kibana to be pretty compelling, simply because it was trivial to get the elk stack up and running and input arbitrary data. I am not as interested in log data, more in business metrics.
I always thought that Elasticsearch was something provided by Amazon, and hence not really interested in it.
So I was rather surprised to see in the title that they raised money.<p>Apparently what Amazon provides is called Elastic <i>MapReduce</i>, not Elastic <i>Search</i>.