Elastic files for IPO

Elastic is roughly similar to MongoDB, in that they’re both document-based datastores, and the companies make money on services.

Elastics point of difference is their main product ElasticSearch, which is an distributed database focussed on search. Text search, ranges, proximity (including lat/long), etc.

For the more technically inclined, it (details excluded) takes a large number of documents and indexes every field of the document, and in particular for text, indexes based on text structures (eg, spaces etc).

Thats not super clear on reading, but if you want to search large quantities of data (I last used it for latitude/longitde-based caching as well as all of our logging), ElasticSearch is your thing. It’s very fast and is definitely the leader in the field.

They’ve stacked several other products with the main ElasticSearch engine, for example, Kibana which is their visualisation tool, and log stash which lets you ingest all your logs into a ‘stash’ ie, Elasticsearch, which you then can search and visualise with Kibana.

Actually, log search and visualisation one of the main use cases with ElasticSearch, but ElasticSearch is a very flexible and fast datastore, so is often used as a cache in front of a more transactional database (eg, SQL, Mongo).

They also have ElasticCloud which is their hosted version of Elastic, similarly to Mongos Atlas.

I’m a big fan of ElasticSearch. They don’t really have a competitor* in their space, if you want search, ElasticSearch is the product.
[* of course they have competitors, but they are easily the default, and I don’t know why anyone would choose an alternative. AWS CloudSearch is an example, but AWS have a hosted ElasticSearch option as well]

The parallels with Mongo are interesting, in that early on MongoDB had a reputation for catastrophic failure and not being suitable for a primary database. ElasticSearch had that same issue, although was never intended as a primary database.

Databases, particularly distributed databases where parts of your data are distributed across many different servers, all controlled by one ‘master’, are hard.

If anyone is interested in more technical detail, what exactly they do etc, I can probably help.

According to SeekingAlpha,
“In the most recent quarter, Elastic reported $56.6M in sales (+79% Y/Y) with a net loss of $18.6M due to increasing costs for R&D, sales, and marketing. In the FY18, revenue grew 81% to $159.9M with a $52.7M net loss”

Mongo (from my software) reported 48.22m in Q2 (48.9% Y/Y), with TTM of 134.75m and a net loss of $29.2 million.