Compare EDB Postgres Advanced Server vs. TimescaleDB in 2026

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Description

A version of PostgreSQL enhanced with security, DBA, and Developer features as well as Oracle database compatibility. Kubernetes allows you to manage deployment, high availability, and automated failover. Postgres containers are lightweight and immutable, allowing you to deploy anywhere. Automate failover, switchovers, backups, recovery and rolling updates. You can move your images and operators to any cloud, so you don't have to be locked in. Our experts can help you overcome containerization and Kubernetes issues. Oracle compatibility allows you to leave your legacy database behind without having to start from scratch. Migrate client applications and databases faster with fewer problems. Tuning and boosting performance can improve the end-user's experience. Deployment on-premises or in the cloud is possible. In a world in which downtime can lead to revenue loss, High-Availability is essential for business continuity.

Description

TimescaleDB brings the power of PostgreSQL to time-series and event data at any scale. It extends standard Postgres with features like automatic time-based partitioning (hypertables), incremental materialized views, and native time-series functions, making it the most efficient way to handle analytical workloads. Designed for use cases like IoT, DevOps monitoring, crypto markets, and real-time analytics, it ingests millions of rows per second while maintaining sub-second query speeds. Developers can run complex time-based queries, joins, and aggregations using familiar SQL syntax — no new language or database model required. Built-in compression ensures long-term data retention without high storage costs, and automated data management handles rollups and retention policies effortlessly. Its hybrid storage architecture merges row-based performance for live data with columnar efficiency for historical queries. Open-source and 100% PostgreSQL compatible, TimescaleDB integrates with Kafka, S3, and the entire Postgres ecosystem. Trusted by global enterprises, it delivers the performance of a purpose-built time-series system without sacrificing Postgres reliability or flexibility.