12 Best InfluxData Alternatives & Competitors (2026)

Elasticsearch with time series data streams handles logs, metrics, and events with powerful search and aggregation capabilities. It supports observability use cases via the Elastic Stack. Compared to InfluxData it provides richer full-text and log correlation features but can be more resource-intensive for pure high-frequency numeric sensor data.

Prometheus is a popular open-source monitoring system and time series database focused on metrics collection via pull-based scraping. It excels in Kubernetes and cloud-native environments with PromQL for alerting and dashboards. Compared to InfluxData, Prometheus offers simpler setup for infrastructure metrics but requires additional components like Thanos or Cortex for long-term retention and high availability at massive scale.

InfluxDB is a popular time-series platform with strong IoT and monitoring focus. It offers a SQL-like language but uses a proprietary storage engine and ecosystem. Compared to QuestDB it provides easier out-of-box dashboards yet lower raw ingest throughput on financial workloads and less emphasis on open Parquet portability.

TimescaleDB extends PostgreSQL with time-series capabilities, combining relational queries and hypertables for IoT and monitoring workloads. It provides strong SQL support and easy integration with existing Postgres ecosystems. Versus InfluxData it may involve higher storage overhead for ultra-high ingest rates but benefits teams already invested in PostgreSQL tooling and complex joins.

ClickHouse is a columnar OLAP database optimized for high-speed analytics on large datasets including time series. It delivers exceptional query performance on historical data and integrates well with data lakes. In comparison to InfluxData, ClickHouse offers broader analytical flexibility but typically needs more configuration for real-time edge ingestion and continuous sensor streams.

Pinot is a real-time distributed OLAP store used for user-facing analytics. It offers low-latency queries but requires more complex setup than QuestDB and provides weaker native support for time-series specific operations like ASOF JOIN.

Apache Druid is a real-time analytics database designed for sub-second queries on streaming event data at scale. It supports ingestion from Kafka and integrates with BI tools. Compared with InfluxData, Druid shines in interactive exploration of large event volumes but may require more operational expertise for continuous high-resolution telemetry pipelines.

DuckDB is an embedded analytical database popular for local Parquet workloads. It offers excellent SQL performance but is not designed as a server for high-throughput ingestion or distributed production use like QuestDB.

VictoriaMetrics is a fast, cost-efficient time series database and monitoring backend compatible with Prometheus remote write. It focuses on high cardinality and long-term storage with lower resource usage. Against InfluxData it offers strong performance for metrics replacement scenarios but less emphasis on edge-to-cloud continuity or physical AI sensor streams.

Materialize is a streaming SQL database for real-time materialized views. It emphasizes correctness over raw speed and does not match QuestDB's specialized order-book arrays or ultra-low latency ingest for market data.

CrateDB combines SQL with document storage for time-series and logs. It provides good horizontal scaling but lacks QuestDB's performance edge on Parquet-native multi-tier storage and trading-specific joins.