time-series database / PostgreSQL extension
TimescaleDB is a PostgreSQL extension that turns Postgres into a high-performance time-series database for real-time analytics.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose Prometheus when you need a self-contained monitoring TSDB with pull-based collection and PromQL instead of SQL on Postgres.
The Prometheus monitoring system and time series database.
Choose ClickHouse when you need a separate, massively scalable columnar SQL engine for real-time analytics over very large time-series or event volumes.
ClickHouse® is a real-time analytics database management system
Choose InfluxDB when you want a purpose-built metrics/event store with its own HTTP API and query language, no Postgres dependency.
Scalable datastore for metrics, events, and real-time analytics
Choose QuestDB when you need high-throughput time-series ingestion with SQL and zero commitment to the PostgreSQL ecosystem.
QuestDB is a high performance, open-source, time-series database
Choose GreptimeDB when you need a unified observability database for metrics/logs/traces with a cloud-native columnar engine.
The open-source observability database. One columnar engine for metrics, logs, and traces, on object storage.
Choose LinDB when you need a lightweight, distributed TSDB tailored to large-scale monitoring workloads.
LinDB is a scalable, high performance, high availability distributed time series database.
Choose TDengine for Industrial IoT scenarios needing a performant, SQL-capable time-series database with cluster support and no Postgres extension.
High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios
Choose VictoriaMetrics when you need a resource-efficient, Prometheus-compatible TSDB that is cheaper to operate in monitoring stacks.
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
Choose Apache IoTDB when you need an IoT-native time-series database with hierarchical schema and embedded deployment options.
Apache IoTDB
Choose CrateDB when you need a distributed SQL database that handles time-series and real-time analytics without Postgres extension lock-in.
CrateDB is a distributed and scalable SQL database for storing and analyzing massive amounts of data in near real-time, even with complex queries. It is PostgreSQL-compatible, and based on Lucene.
These projects were analysed and named timescaledb among their alternatives. The relationship is not symmetric — how timescaledb rates them is a separate judgement, made when timescaledb is analysed in its own right.
calls timescaledb “Choose if you want to add time-series hypertables to PostgreSQL, gaining full SQL and joins rather than a standalone TSDB.”
High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios
calls timescaledb “Choose when you want PostgreSQL compatibility plus time-series partitioning/compression and prefer SQL over a purpose-built Prometheus storage engine.”
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
calls timescaledb “Postgres extension enabling time-series SQL; choose it when you want one SQL layer over your relational and time-series data.”
The open-source observability database. One columnar engine for metrics, logs, and traces, on object storage.
calls timescaledb “Choose it when you already run PostgreSQL and want time-series as an extension rather than a separate TSDB.”
Apache IoTDB