Earlier last week I was working on a python package that would compress numerical series into strings (and back). The package is now available on Github. It gets you around ~80% compression. It is useful to store or transmit stock prices, monitoring & other time series data in compressed string format.
Elasticsearch is primarily known for it’s search capabilities but it’s also very well suited for storage, aggregation, and querying of time series data. In this tutorial, we’ll learn how to use Elasticsearch to store simple metrics and visualize them with Kibana.
To summarize, we’ll generate dummy signup data with this script. Ingest it into locally running Elasticsearch. Use Kibana to visualize the data in different ways. For simplicity, we are not using Logstash in this tutorial but you can easily configure the same data to be ingested through Logstash. Let’s dive in!