TimescaleDB is a PostgreSQL‑extension that adds scalable time‑series capabilities. Looking for other backend/database platforms that can handle time‑series, analytics, or high‑throughput workloads? Below are 20 strong alternatives.
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The powerful open‑source relational database. With native extensions (e.g., pg_partman) it can handle time‑series workloads without a dedicated engine.
Purpose‑built open‑source time‑series database offering high‑write throughput, down‑sampling, and a SQL‑like query language (Flux).
Column‑oriented OLAP database designed for real‑time analytics on massive datasets, frequently used for time‑series data.
High‑performance analytics data store optimized for low‑latency slice‑and‑dice queries on event‑level data.
Fast, open‑source relational database for time‑series data with a PostgreSQL wire protocol and SQL support.
Scalable, high‑performance time‑series database and monitoring solution compatible with Prometheus remote write API.
Open‑source monitoring system and time‑series database focused on metrics collection and alerting.
Distributed NoSQL database offering high availability and linear scalability, often used for large‑scale time‑series workloads.
Document‑oriented database with flexible schema; supports time‑series collections for efficient storage and queries.
Redis module that adds a fast, in‑memory time‑series data structure with aggregation and down‑sampling capabilities.
Distributed SQL database with strong consistency and survivability; can be used for time‑series data at scale.
Open‑source, PostgreSQL‑compatible distributed SQL database that combines OLTP and OLAP workloads, suitable for time‑series.
MySQL‑compatible, horizontally scalable NewSQL database offering HTAP capabilities for mixed analytical and transactional workloads.
Distributed SQL database built on Elasticsearch, optimized for IoT and time‑series data with full‑text search.
Real‑time distributed OLAP datastore designed for low‑latency analytics on streaming data.
Cloud data warehouse with native support for semi‑structured and time‑series data, offering elastic scaling and separation of compute/storage.
Fully managed serverless data warehouse with high‑speed SQL analytics; supports time‑series via partitioned tables.
Fully managed time‑series database service optimized for IoT and operational applications, with built‑in tiered storage.
Fast, fully managed analytics service for large‑scale telemetry and log data, offering a powerful query language.
In‑memory relational database delivering sub‑millisecond response times, often used for high‑frequency time‑series workloads.