observability database / time-series storage
GreptimeDB is an open-source observability database that stores metrics, logs, and traces in one columnar engine on object storage, queryable with SQL/PromQL.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
same columnar object-store engine for logs, metrics and traces; choose it if you prefer AGPL and its native API over SQL/PromQL.
Parseable is an open source, unified infrastructure observability platform built in Rust on a data lake architecture. It tracks logs, metrics, traces, and events across apps, agents, and systems, reducing storage costs by up to 90% through columnar telemetry compression.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
general-purpose columnar SQL engine; choose it if you need a battle-tested analytics DB for pooled observability and non-observability workloads, accepting you must build ingestion/schema yourself.
ClickHouse® is a real-time analytics database management system
Postgres extension enabling time-series SQL; choose it when you want one SQL layer over your relational and time-series data.
A time-series database for high-performance real-time analytics packaged as a Postgres extension
Lucene-based distributed SQL database; choose it if you need full-text log search combined with SQL, but you'll assemble your own pipeline.
CrateDB is a distributed and scalable SQL database for storing and analyzing massive amounts of data in near real-time, even with complex queries. It is PostgreSQL-compatible, and based on Lucene.
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Java time-series DB for fast SQL over large metric/event streams; choose it for metrics-only workloads when you don't need GreptimeDB's object-storage log/trace model.
QuestDB is a high performance, open-source, time-series database
metrics-only distributed time-series DB in Go; choose it for a simpler metrics backend if you don't need logs/traces.
LinDB is a scalable, high performance, high availability distributed time series database.
standard pull-based monitoring system with its own local TSDB; choose it for basic metrics when federation/HA is not required.
The Prometheus monitoring system and time series database.
metrics/events TSDB with Flux/InfluxQL ecosystem; choose it for metrics-only applications on your own stack rather than unified log/trace storage.
Scalable datastore for metrics, events, and real-time analytics
PromQL-compatible metrics DB component; choose it for a production-proven metrics backend and run VictoriaLogs separately for logs.
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
IoT/IIoT oriented time-series DB; choose it for high-cardinality sensor metrics, but not for log/trace observability.
High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios
IoT/edge time-series DB; choose it for industrial data collection, not a unified observability engine.
Apache IoTDB
long-term Prometheus metrics backend with optional HA; choose it for metrics storage only, not logs/traces.
Grafana Mimir provides horizontally scalable, highly available, multi-tenant, long-term storage for Prometheus.
search-engine database on S3 for logs/traces; choose it when you need full-text search and don't require metrics/PromQL.
Cloud-native OSS search engine for observability
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
observability platform service with UI/Pipelines/alerts; choose it for a full product rather than raw database.
Open source observability platform for logs, metrics, traces, frontend monitoring, pipelines and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.
LLM-query observability app on S3; choose for natural-language exploration, not a programmable DB.
Monoscope lets you ingest and explore your logs, traces and metrics. We store these in S3 compatible buckets. Query in natural language via LLMs.
OpenTelemetry observability platform with APM/UI; choose for a turnkey full-stack product.
SigNoz is an open-source, OpenTelemetry-native observability platform for your team and their AI agents. Get logs, metrics, and traces in one tool with features like APM, distributed tracing, log management, infra monitoring, etc. Combined with SigNoz MCP and a native AI teammate (in SigNoz Cloud) it helps you build more resilient apps.
OpenTelemetry APM product with UI; choose for trace-centric monitoring, not as an embeddable data engine.
Open source APM: OpenTelemetry traces, metrics, and logs
observability platform with session replay on ClickHouse; choose for end-user experience, not as a library.
Resolve production issues, fast. An open source observability platform unifying session replays, logs, metrics, traces and errors powered by ClickHouse and OpenTelemetry.
self-hosted monitoring/alerting tool with dashboards; choose for infrastructure monitoring, not as an embedded observability database.
An AI-powered next-generation open source real-time observability system.
These projects were analysed and named greptimedb among their alternatives. The relationship is not symmetric — how greptimedb rates them is a separate judgement, made when greptimedb is analysed in its own right.
calls greptimedb “Choose if you want an Apache-2.0 cloud-native TSDB that unifies metrics, logs, and traces with SQL, designed for observability workloads.”
High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios
calls greptimedb “When you want a unified Rust columnar database for metrics, logs, and traces with native OpenTelemetry support and object storage.”
Scalable datastore for metrics, events, and real-time analytics
calls greptimedb “Choose GreptimeDB when you need a unified observability database for metrics/logs/traces with a cloud-native columnar engine.”
A time-series database for high-performance real-time analytics packaged as a Postgres extension
calls greptimedb “Choose when you want a unified columnar engine for metrics, logs, and traces on object storage and can accept a younger, broader observability database.”
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
calls greptimedb “Choose when you need SQL/TSDB-style queries over metrics, logs, and traces in one columnar database.”
Cloud-native OSS search engine for observability
calls greptimedb “Choose it for cloud-native observability on object storage when you need metrics/logs/traces in one engine instead of IoTDB's industrial focus.”
Apache IoTDB