The best MariaDB Enterprise Analytics alternatives

CrateDB may suit teams analyzing live operational data across varied data types, including time-series, JSON, and geospatial data.

Exasol suits organizations needing multi-departmental analytics, in-database machine learning or AI, or complex data integration and virtualization.

InfluxDB 3 may suit teams handling timestamped data for industrial operations, observability, or AI applications.

GreptimeDB is suited to teams handling time-indexed observability or IoT data who want SQL and PromQL querying.

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

It suits enterprises with demanding analytics workloads and data residency or security requirements.

Druid may suit teams building low-latency analytics for streaming or batch data, especially workloads involving high query concurrency or immediate…

MonetDB suits organizations and researchers needing a self-hosted SQL database for analytics or bulk processing.

MotherDuck suits data teams, app developers, and AI agents needing a cloud data warehouse built on DuckDB.

Redshift suits teams running SQL analytics, dashboards, data sharing, application development, or ETL jobs.

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

Firebolt suits engineers choosing between self-managed analytical database deployments and a managed service, including teams working with open…

Kudu suits teams building self-hosted analytical systems for data that changes frequently.

Pinot suits teams building real-time analytics or user-facing workloads that combine batch and streaming data.

It suits teams building self-hosted analytical systems for real-time, high-concurrency, or ad hoc SQL workloads.

It suits organizations that need to unify customer profiles and activate permissioned data across engagement systems.