timescale/promscale

[DEPRECATED] Promscale is a unified metric and trace observability backend for Prometheus, Jaeger and OpenTelemetry built on PostgreSQL and TimescaleDB.

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Summary Information

Updated 43 minutes ago
Added to GitGenius on March 27th, 2022
Created on April 3rd, 2020
Open Issues & Pull Requests: 131 (+0)
Number of forks: 172
Total Stargazers: 1,313 (+0)
Total Subscribers: 6 (+0)

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Issue Activity (beta)

Open issues: 22
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,388 days
Stale 30+ days: 22
Stale 90+ days: 22

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Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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  • Bug (37)
  • Improvement (28)
  • Feature (14)
  • Performance (11)
  • Question (10)
  • Documentation (7)
  • prom-migrator (6)
  • good first issue (5)

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Detailed Description

Promscale is a deprecated unified observability backend written in Go that integrated metric and trace storage capabilities for Prometheus, Jaeger, and OpenTelemetry systems. Built on PostgreSQL and TimescaleDB, it provided a consolidated platform for organizations seeking to manage both metrics and distributed traces through a single backend system.

The repository was designed to address a key gap in observability infrastructure by eliminating the need for separate storage systems for different telemetry types. Promscale functioned as a 100% PromQL-compliant Prometheus remote storage backend while simultaneously serving as a certified Jaeger storage backend. This dual capability meant organizations could ingest metrics through Prometheus remote write protocols and traces through Jaeger collectors or the OpenTelemetry Protocol, storing both in the same PostgreSQL-based system. The architecture consisted of just two components: the Promscale Connector and the Promscale Database, intentionally kept simple to reduce operational complexity compared to alternatives like Elasticsearch or Cassandra for trace storage.

For Prometheus users, Promscale offered centralized metric storage across multiple Kubernetes clusters with multi-tenancy support, enabling single-pane-of-glass visibility. It supported PromQL alerting rules, recording rules for downsampling, and per-metric retention policies to optimize storage costs and query performance for long-term trend analysis. The system could scale to millions of series and hundreds of thousands of samples per second on a single PostgreSQL node through TimescaleDB's optimization capabilities.

For Jaeger and OpenTelemetry users, Promscale provided durable and scalable trace storage with native OTLP support. A distinctive feature was the ability to query traces using SQL, enabling deeper trace analysis beyond Jaeger's built-in filtering capabilities. The system supported Service Performance Management features in Jaeger and included an Application Performance Management experience in Grafana with customizable dashboards built on SQL queries against trace data.

The most actively tracked issue label was Deprecation, with one item recorded, underscoring the project's end-of-life state.