Best Time-Series Databases 2026

DolphinDB suits teams that need real-time analytics or stream processing, including those working in finance, energy, transportation, manufacturing, or scientific…

QuestDB may suit teams handling time-series data in low-latency settings, including capital-markets firms, digital-asset businesses, energy operators, aerospace…

CnosDB may suit teams collecting and querying time-oriented data for the listed IoT, industrial, vehicle, or IT operations uses.

LinDB suits teams building IoT or IT operations monitoring systems that need to store and analyze numeric time-series metrics.

Warp 10 suits teams managing sensor or other time series data on their own infrastructure.

openGemini suits teams analyzing time-series data for monitoring, observability, IoT, or operations.

Prometheus suits teams that need to collect and query system metrics or set up alerts.

Timestream suits teams building time-series workloads such as IoT telemetry, real-time monitoring, analytics, or predictive maintenance.

kdb+ suits organizations handling time-series workloads in areas such as trading, fraud detection, IoT monitoring, and other listed sectors.

RRDtool suits developers and administrators who need self-hosted time-series logging, retention policies, and graphing through command-line tools or supported language…

It suits teams needing a self-managed time-series system with PromQL, Kafka or Influx ingestion, retention policies, and horizontal scaling.

BTrDB suits developers and operators working with dense telemetry who can deploy and manage a self-hosted database.

M3 suits teams operating Prometheus-based monitoring that need centralized, scalable metrics storage and long retention.

It suits engineers and operations staff managing large computer systems who want self-hosted, horizontally scalable time-series storage.