MariaDB 11.7: The Fork That Keeps Its Own Path

Actualizado: 2026-05-03

MariaDB 11.7 (November 2024) is a release that consolidates the fork’s independent direction from MySQL. Three areas receive primary attention: natively integrated vector search — without additional extensions —, substantial improvements to JSON support, and query engine optimisations that translate to 5-15% performance improvements in benchmarks vs 11.5. For teams that chose MariaDB years ago and wonder whether to stay or migrate, this version clarifies the argument.

Key takeaways

• Native vector search with HNSW index: MariaDB 11.7 supports similarity search without external extensions, while MySQL only offers it through HeatWave.
• JSON_OBJECT_AGG and JSON path improvements bring MariaDB closer to functional parity with PostgreSQL JSONB for many use cases.
• The divergence from MySQL keeps growing: Galera multi-master vs Group Replication, real pluggable storage vs InnoDB-centred, community licence vs Oracle-backed.
• MariaDB is not always better than PostgreSQL or MySQL: each database has its strengths and optimal use cases.
• Application compatibility with MySQL remains high for standard CRUD operations; divergence appears in advanced features.

Vector search: the most relevant new feature

The vector search integrated in MariaDB 11.7 is the change most affecting the decision map for teams already running MariaDB in production who are evaluating where to store embeddings for RAG applications or semantic search.

The syntax is extended standard SQL:

-- Create table with vector column
CREATE TABLE documents (
    id INT PRIMARY KEY AUTO_INCREMENT,
    title VARCHAR(255),
    content TEXT,
    embedding VECTOR(384)
);

-- Create HNSW index for efficient search
ALTER TABLE documents ADD VECTOR INDEX idx_embedding (embedding)
    WITH (M=16, EF_CONSTRUCTION=200);

-- Insert with embedding
INSERT INTO documents (title, content, embedding)
VALUES ('Introduction to eBPF',
        'eBPF allows executing code in the kernel...',
        VEC_FromText('[0.12, 0.34, -0.56, ...]'));

-- Similarity search
SELECT id, title,
       VEC_DISTANCE_EUCLIDEAN(embedding, VEC_FromText('[...]')) AS distance
FROM documents
ORDER BY distance
LIMIT 10;

The HNSW (Hierarchical Navigable Small World) index is the same algorithm used by pgvector and most specialised vector databases. For teams already running MariaDB who want to add semantic search without adding a separate vector database, this change eliminates an infrastructure component.

Current limitations: MariaDB 11.7’s vector search is functional but still immature compared to pgvector in terms of index options, available distance metrics, and performance at very high cardinality. For serious production, evaluate whether performance is sufficient for your specific scale before committing.

JSON improvements

The most useful addition in 11.7 is JSON_OBJECT_AGG, which aggregates rows into a JSON object:

SELECT user_id,
       JSON_OBJECT_AGG(key, value) AS preferences
FROM user_configuration
GROUP BY user_id;

-- Result: {"theme": "dark", "language": "en", "notifications": "1"}

Along with improvements to JSON path expressions and faster JSON operations, MariaDB 11.7 narrows the gap with PostgreSQL JSONB for use cases storing semi-structured data in JSON fields. It does not reach full parity — PostgreSQL has a richer JSON function ecosystem and more flexible GIN indexes on JSONB fields — but the practical difference shrinks for most common uses.

Query engine optimisations

The optimiser improvements in 11.7 are most noticeable in multi-table joins, correlated subqueries, and covering index usage. The MariaDB project benchmarks show 5-15% improvements over 11.5 on read-intensive workloads; improvements are smaller on pure write workloads.

MariaDB vs MySQL 8: growing divergence

Galera Cluster: the HA differentiator

For teams needing distributed writes across multiple nodes with strong consistency, Galera Cluster remains the hardest argument to match in the MySQL/MariaDB ecosystem. MySQL Group Replication covers similar cases, but Galera has more production track record and a more active community of operators.

Conclusion

MariaDB 11.7 strengthens the argument for staying on MariaDB if you are already using it: native vector search without additional extensions, substantial JSON improvements, and incremental performance that justifies the upgrade effort. The argument for migrating to MySQL or PostgreSQL must be based on specific needs MariaDB does not cover, not on MySQL being “the original” or PostgreSQL being “the modern option”. For web workloads with read replicas and Galera for HA, MariaDB 11.7 is a robust and actively developed platform.