MariaDB
About MariaDB
MariaDB offers a database platform including open source and enterprise database software. The platform supports multiple database workloads and data types. MariaDB is compatible with MySQL and Oracle. The company provides deployment options ranging from self-managed to fully managed cloud service. MariaDB also provides support, services and migration tools alongside its database products.
Products
- MariaDB Enterprise Server: Core open source database supporting transactional, analytical and mixed workloads for relational, JSON and vector data models.
- MariaDB Cloud: Fully managed database-as-a-service with provisioned and serverless architecture options.
- MariaDB MaxScale: Database proxy providing high availability, scalability and security for MariaDB databases.
- MariaDB Enterprise Cluster: Active-active, multi-master synchronous replication solution powered by Galera.
- MariaDB Exa: Combines MariaDB Enterprise with an MPP columnar engine for analytics on live operational data.
- MariaDB Community Server: Open source database server intended for non-production applications.
Used for
- Running mission-critical applications on the database.
- Migrating from legacy or proprietary databases such as Oracle or Oracle MySQL.
- Ingesting data and delivering AI answers grounded in data via a REST API.
- Performing standard database tasks and AI operations such as semantic search.
- Monitoring databases through dashboards, alerts and metric exports.
Who it is for
- Financial services organizations handling complex financial data and transactions.
- Public sector organizations with complex data management needs.
- DBAs and developers.
- Banking institutions and telecom networks.
From MariaDB's own website, read 2026-10-24. How we build listings.
How to evaluate Data Warehouse & Lakehouse
This is how the CIOPages Research Team evaluates this category. It is not an assessment of MariaDB. The category covers two kinds of product, so both frameworks are here. Most buyers need one of them.
Cloud Data Warehouse
25%
Query Performance & Concurrency
TPC-DS benchmarks, concurrent user support, query queuing, automatic scaling, sub-second response for dashboards
20%
Data Ingestion & Integration
Streaming ingestion (Kafka, Kinesis), batch loading, CDC support, native connectors, data sharing/marketplace
20%
Governance & Security
Column/row-level security, dynamic data masking, data lineage, access policies, audit logging, compliance certifications
15%
AI/ML Integration
Native ML runtimes (Python/Spark), feature store, vector search, LLM integration, model serving
10%
Cost Management
Compute/storage separation, auto-suspend, resource monitors, usage attribution, reserved capacity pricing
10%
Ecosystem & Tooling
BI tool compatibility, dbt/Airflow integration, Iceberg/Delta support, partner ecosystem, marketplace
Data Lakehouse Platforms
25%
Open Format & Catalog Interoperability
Native read AND write to Apache Iceberg and/or Delta Lake, Iceberg REST Catalog support, credential vending for external engines, cross-format bridges (Delta UniForm, Apache XTable), and whether grants and lineage travel with the table when another engine reads it
20%
Query Engine Performance & Concurrency
Vectorized execution (Photon, Arrow/Gandiva, native engines), caching and materialization (reflections, result cache, Warp Speed), high-concurrency BI behavior, autoscaling, and predictable performance on your own data — not vendor benchmarks
20%
Data Engineering, Streaming & AI/ML
Batch and streaming ingestion into open tables, incremental/CDC and upsert support, orchestration, ML lifecycle (feature store, training, model serving), notebook and Python/Spark depth, and native LLM/agentic and vector capabilities
15%
Governance, Security & Lineage
A unified catalog spanning tables, files, ML models and (increasingly) unstructured data; fine-grained RBAC/ABAC, row/column masking, data sharing, automated lineage, and consistent policy enforcement across every engine that touches the data
10%
Operational Simplicity & Table Maintenance
Automated compaction, clustering, snapshot expiry and orphan-file cleanup; serverless vs. cluster sizing; multi-cloud and hybrid/on-prem reach; admin and FinOps tooling; and how much table toil the team must own versus the platform absorbing it
10%
Cost Model & Consumption Control
Consumption unit (DBU, credit, capacity unit, bytes/slots), separation of storage and compute, idle-suspend and autoscaling guardrails, egress and cross-region exposure, workload isolation, and the FinOps tooling to attribute and cap spend
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Quick Facts
mariadb.com Pricing pageCategoryData & Analytics
SubcategoryData Warehouse & Lakehouse
DeploymentSaaS, Self-hosted
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