M3DB vs QuestDB
No clear leader: M3DB (50.5) and QuestDB (49.9) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for time-series databases. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
M3DB
M3 is a distributed time series database built for storing and querying high-volume metrics with multiple query languages. It can be deployed as a single node or multi-node cluster using Docker, Kubernetes, or binaries.
QuestDB
A specialized database engineered to ingest high-volume time-series data at speed, execute queries with minimal latency, and maintain queryable history across tiered storage layers—combining standard SQL with open file formats for portability.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
M3DB
- Prometheus
- Graphite
- Kubernetes
- Docker
- InfluxDB
- etcd
QuestDB
- PostgreSQL
- Parquet
- Arrow
- Polars
- Pandas
- Debezium
- Iceberg
- MySQL
- MongoDB
- Cassandra
- Kafka
- Apache Parquet
- Apache Arrow
- Claude Code
- REST API
- Apache Iceberg
- Databricks
- AWS
- Azure
M3DB or QuestDB: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.