Best Time-Series Databases in 2026

Apache IoTDB

IoT teams that need time-series storage across edge and cloud environments may find IoTDB relevant, particularly in the listed industrial scenarios.

BTrDB suits teams self-hosting clustered storage for dense streaming telemetry, including high-precision sensor or smart-grid data.

TDengine

TDengine is designed for industrial enterprises and organizations running traditional data historians or legacy industrial IoT platforms.

LinDB

LinDB suits teams collecting and analyzing numeric metrics for IoT or IT operations across infrastructure and application layers.

CnosDB

CnosDB suits teams managing time-series data for the listed IoT, industrial, vehicle, or IT operations uses.

InfluxDB

InfluxDB suits teams working with timestamped data for industrial operations, observability or AI applications.

openGemini

openGemini suits teams managing time-series workloads for observability, IoT, or operations analysis, especially those needing distributed scaling and multiple ingestion routes.

It suits teams building real-time analytics or stream-processing systems across the listed industries, including deployments that need horizontal scaling or high availability.

It suits teams needing self-managed, horizontally scalable time-series infrastructure with PromQL, Kafka, or Influx Line Protocol inputs.

OneTick

OneTick is aimed at hedge funds, proprietary trading firms, brokers, banks, asset managers, data marketplaces, and exchanges.

QuestDB

QuestDB suits teams building time-series workloads that need SQL querying and low-latency ingestion.

VictoriaMetrics

It suits teams that need metrics monitoring and storage, or organizations building observability across metrics, logs, and traces.

Warp 10

Warp 10 suits teams collecting and analyzing sensor or other time-series data, especially those needing self-hosting, multiple deployment modes, or data-science and dashboard integrations.

GreptimeDB suits teams handling time-indexed observability or IoT data that want SQL and PromQL querying.

kdb+

kdb+ suits teams analyzing high-volume time-series data in finance, fraud, industrial monitoring, or related sectors.

Prometheus

It suits teams that need open-source metrics collection, querying and alerting, including self-hosted deployments.