I used to work at a data analysis startup called Jut. Jut’s vision was to bring all your data together in a single environment. This enabled integrated analysis using our programming language, Juttle. It was challenging because there are many different types of data. Different data types require different models for optimal storage and querying. At the highest level, Jut divided all data into two kingdoms: metrics and events. Today I’ll cover the design and implementation of the metrics side, which was covered by a database named Orestes that we built.
Continue reading “Orestes: a Time Series Database Backed by Cassandra and Elasticsearch”