time-series database / IoT data storage
TDengine is a high-performance, cloud-native, distributed time-series database designed for Industrial IoT and IoT scenarios, supporting SQL, stream processing, and data storage at massive scale.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Choose if you want a thriving TSDB with SQL support in InfluxDB 3.0 and an Apache-2.0 license, and can scale OSS without built-in clustering.
Scalable datastore for metrics, events, and real-time analytics
Choose if you need extremely fast single-node SQL queries for time series and do not require distributed scaling in the OSS edition.
QuestDB is a high performance, open-source, time-series database
Choose if you want an Apache-2.0 cloud-native TSDB that unifies metrics, logs, and traces with SQL, designed for observability workloads.
The open-source observability database. One columnar engine for metrics, logs, and traces, on object storage.
Choose if you want an Apache-licensed TSDB from the Apache ecosystem with an IoT-optimized data model and cluster support.
Apache IoTDB
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose if you need a pull-based monitoring stack with PromQL and ecosystem tools, not a SQL-capable IoT database.
The Prometheus monitoring system and time series database.
Choose if you already run ClickHouse and want OLAP-grade SQL analytics, accepting manual time-series schema management.
ClickHouse® is a real-time analytics database management system
Choose if you want to add time-series hypertables to PostgreSQL, gaining full SQL and joins rather than a standalone TSDB.
A time-series database for high-performance real-time analytics packaged as a Postgres extension
Choose if you want a distributed TSDB focused on metrics with low latency and lightweight query language, not full SQL.
LinDB is a scalable, high performance, high availability distributed time series database.
Choose if you want a distributed SQL database with flexible schema for mixed workloads, not a purpose-built time-series engine.
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.
Choose if you want a cost-effective, PromQL-compatible monitoring TSDB with high performance and low resource use, not SQL.
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose if you support legacy HBase-based infrastructure needing a classic TSDB, accepting no active development.
A scalable, distributed Time Series Database.
Choose if you need an Apache-2.0 distributed TSDB and can accept a codebase that is no longer actively maintained.
Apache HoraeDB (incubating) is a high-performance, distributed, cloud native time-series database.
These projects were analysed and named TDengine among their alternatives. The relationship is not symmetric — how TDengine rates them is a separate judgement, made when TDengine is analysed in its own right.
calls TDengine “Choose it for Industrial IoT workloads with SQL when you can accept AGPL-3.0 instead of Apache-2.0.”
Apache IoTDB
calls TDengine “Choose TDengine for Industrial IoT scenarios needing a performant, SQL-capable time-series database with cluster support and no Postgres extension.”
A time-series database for high-performance real-time analytics packaged as a Postgres extension
calls TDengine “Choose for Industrial IoT time-series workloads needing a specialized clusater DB with SQL support, rather than Prometheus-centric monitoring storage.”
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
calls TDengine “IoT/IIoT oriented time-series DB; choose it for high-cardinality sensor metrics, but not for log/trace observability.”
The open-source observability database. One columnar engine for metrics, logs, and traces, on object storage.