Where to store high-cardinality metrics?

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/sre

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  • signoz

    SigNoz is an open-source APM. It helps developers monitor their applications & troubleshoot problems, an open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool

    You should try filtering and aggregating span data directly. A columnar store with the right indexes should provide blazing-fast queries. We are building SigNoz and chose ClickHouse due to high-cardinality filtering and faster aggregates with fast ingestion. Honeycomb should also perform fast due to similar reasons.

  • Elasticsearch

    Free and Open, Distributed, RESTful Search Engine

    Elasticsearch. The storage overhead has been significantly improved with their new TSDB work: https://github.com/elastic/elasticsearch/issues/74660

  • InfluxDB

    Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.

  • cortex

    A horizontally scalable, highly available, multi-tenant, long term Prometheus. (by cortexproject)

    Cortex is not really good for high-cardinality metrics (if you are talking about https://github.com/cortexproject/cortex)

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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