InfluxDB
Best for self-hosting
Why teams pick it
Control your scheduling stack on your own infrastructure.
Open-source alternatives to Quasar
Compare community-driven replacements for Quasar in time-series databases workflows. We curate active, self-hostable options with transparent licensing so you can evaluate the right fit quickly.
Quasar
Quasar ingests nonstop numeric data, applies advanced compression, and exposes fast queries for operational analytics, forecasting, and AI features. It’s built for sub-second access over massive time-series workloads, reducing warehouse/storage costs while powering dashboards and models across IoT, finance, and manufacturing.Read more
Key stats
- 10Alternatives
- 1Support self-hosting
Run on infrastructure you control
- 10Active development
Recent commits in the last 6 months
- 7Permissive licenses
MIT, Apache, and similar licenses
Counts reflect projects currently indexed as alternatives to Quasar.
Start with these picks
These projects match the most common migration paths for teams replacing Quasar.
TimescaleDB
Privacy-first alternative
Why teams pick it
Keep customer data in-house with privacy-focused tooling.
All open-source alternatives
CnosDB
High-performance distributed time-series database for IoT and observability
Active developmentIntegration-friendlyRust
Why teams choose it
- Unlimited time-series scalability with advanced timeline aggregation and configurable caching
- Standard SQL interface with schema-less writes and out-of-order data support
- Cloud-native distributed architecture with storage-compute separation and horizontal scaling
Watch for
Requires Rust toolchain, CMake, FlatBuffers, and Protobuf for source builds
Migration highlight
IoT Sensor Network Monitoring
Ingest millions of sensor readings per second with automatic compression, query historical trends via SQL, and cache recent values for real-time dashboards.
QuestDB
Blazing‑fast time‑series database for real‑time analytics with low‑latency SQL
Active developmentPermissive licenseFast to deployJava
Why teams choose it
- Sub‑millisecond ingestion of millions of rows per second
- Vectorized, SIMD‑accelerated SQL engine with time‑series extensions
- Multi‑tier storage: WAL → native columnar → Parquet on object storage
Watch for
Enterprise features require paid license
Migration highlight
Real‑time crypto trade analytics
Ingests millions of trade events per second and serves sub‑second queries for live price charts via Grafana.
tstorage
Fast, goroutine-safe on-disk time-series storage for Go
Active developmentPermissive licenseIntegration-friendlyGo
Why teams choose it
- Goroutine-safe ingestion with nanosecond-level performance
- Automatic time-partitioning keeps recent data in memory and older data on disk
- Simple API supporting labeled metrics and configurable timestamp precision
Watch for
Limited to the Go ecosystem; no native bindings for other languages
Migration highlight
Load-testing metrics collection
Capture millions of latency points with sub-microsecond write latency, keeping heap usage stable.
openGemini
Scalable, high-performance time-series DB for massive telemetry
Active developmentPermissive licenseFast to deployGo
Why teams choose it
- High performance with LSM storage and automatic partitioning
- MPP architecture for linear horizontal scalability
- High‑cardinality engine with up to 15:1 columnar compression
Watch for
Maturing project as a CNCF sandbox, ecosystem still growing
Migration highlight
Industrial sensor data collection
Ingest millions of sensor readings per second with sub-10 ms query latency, enabling real-time monitoring and anomaly detection.
Prometheus
Flexible monitoring system with powerful queries and autonomous servers
Active developmentPermissive licenseFast to deployGo
Why teams choose it
- Multi‑dimensional time‑series data model
- PromQL – powerful query language
- Autonomous single‑server operation
Watch for
Scaling beyond a single node requires federation
Migration highlight
Cluster health monitoring
Continuously scrapes node and pod metrics, alerts on resource exhaustion, and visualizes trends via Grafana.
GreptimeDB
Unified observability database for metrics, logs, and traces
Active developmentPermissive licenseIntegration-friendlyRust
Why teams choose it
- Unified storage for metrics, logs, and traces as timestamped wide events
- Sub-second query performance at petabyte scale with distributed Rust engine
- Cloud-native architecture with compute/storage separation and object storage support
Watch for
Currently in beta status with GA planned for mid-2025
Migration highlight
Unified Observability Platform
Replace separate Prometheus, Elasticsearch, and tracing backends with one database, reducing operational complexity and infrastructure costs
TDengine
High‑performance, cloud‑native time‑series database for IoT scale
Active developmentIntegration-friendlyAI-powered workflowsC
Why teams choose it
- High‑performance ingestion and columnar compression
- Built‑in AI agent (TDgpt) for forecasting and anomaly detection
- Cloud‑native distributed architecture with RAFT and Kubernetes support
Watch for
Windows support limited to enterprise edition
Migration highlight
Real‑time fleet telemetry processing
Ingests millions of vehicle metrics per minute, runs on‑edge compute, and provides predictive alerts via TDgpt.
TimescaleDB
PostgreSQL extension delivering high-performance real-time analytics on time-series data
Active developmentPrivacy-firstFast to deployC
Why teams choose it
- Hypertables with automatic time‑based partitioning
- Hybrid row‑columnar storage delivering >90 % compression
- Continuous aggregates for incremental materialized views
Watch for
Learning curve for hypertable design and policies
Migration highlight
IoT Device Telemetry Monitoring
Ingest millions of sensor readings per day, query recent trends instantly, and retain historic data at 90 % reduced storage.
InfluxDB
Real-time time series database for events and metrics
Self-host friendlyActive developmentPermissive licenseRust
Why teams choose it
- Sub-10ms last-value queries with diskless object storage architecture
- SQL and InfluxQL query engines with FlightSQL and HTTP API support
- Embedded Python VM for custom plugins, triggers, and data transformations
Watch for
Relatively new GA release (April 2025) with evolving feature set
Migration highlight
Server Infrastructure Monitoring
Operations teams visualize CPU, memory, and disk metrics across thousands of servers with real-time dashboards updating every second.
CrateDB
Distributed SQL database for real-time analytics at scale
Active developmentPermissive licenseIntegration-friendlyJava
Why teams choose it
- Standard SQL with PostgreSQL wire protocol and HTTP API support
- Horizontal scalability with auto-sharding, auto-replication, and self-healing
- Native time-series, full-text search, and geospatial capabilities
Watch for
Requires understanding of distributed database concepts for optimal deployment
Migration highlight
IoT Sensor Data Analytics
Ingest thousands of sensor readings per second and run real-time SQL queries for anomaly detection and trend analysis across distributed clusters.
Choosing a time-series databases alternative
Teams replacing Quasar in time-series databases workflows typically weigh self-hosting needs, integration coverage, and licensing obligations.
- 1 project let you self-host and keep customer data on infrastructure you control.
- 10 options are actively maintained with recent commits.
Tip: shortlist one hosted and one self-hosted option so stakeholders can compare trade-offs before migrating away from Quasar.