Comparing InfluxDB, TimescaleDB, and QuestDB Timeseries Databases
A high-level overview of timeseries databases to compare features, functionality, maturity, and performance
We’re living in the golden age of databases, as money is flowing into the industry at historic rates (e.g. Snowflake, MongoDB, Cockroach Labs, Neo4j). If the debate between relational vs. non-relational or online analytical processing (OLAP) vs. online transaction processing (OLTP) ruled the past decade, a new type of databases has been steadily growing in popularity. According to DB-Engines, an initiative to collect and present information on database management systems, timeseries databases are the fastest growing sector since 2020:
Timeseries databases (TSDB) are databases optimized to ingest, process, and store time-stamped data. Such data may include metrics from servers and applications, readings from IoT sensors, user interaction on a website or an app, or trading activity on financial markets. Timeseries workloads are usually characterized by the following properties:
- Each data point includes a timestamp that can be used to index, aggregate, and sample. This data can also be multi-dimensional and correlated.
- High write-speed (ingestion) is preferred to capture data at high…
