Time Series Databases store and retrieve sequences of data points indexed by time. These tools handle high volumes of metrics, logs, and traces to enable real-time observability and analytics. This type of software solves the problem of querying vast amounts of time-stamped information without performance degradation. DevOps engineers and system administrators use these apps to monitor infrastructure health. Self-hosting these databases ensures that sensitive system logs and performance metrics remain on private hardware instead of on external servers.
This page lists 2 open source tools in the Time Series Databases category. The most popular are Apache Druid and GreptimeDB. Most use the Apache-2.0 license, and 2 offer an official Docker image.
A high performance real-time analytics database designed for fast queries and high concurrency data ingestion.
A cloud-native observability database that unifies metrics, logs, and traces into a single data model.
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