Nine workloads.
One engine.
The AI-Native Unified Database. A single binary that replaces your relational, analytical, time-series, vector, search, and streaming systems.
MonkDB unifies the data plane that AI systems and operational workloads need. Identity, policy, and lineage run inside the engine. Vector and SQL share the same query surface. The same binary deploys from cloud to edge.
Every data shape your AI stack needs, served from one engine
Nine workloads, one query surface, one storage layer. No sidecar systems, no embedding drift, no pipeline glue between data shapes that your applications actually use together.
Relational
ACID transactions, joins, and SQL across the unified plane.
Time-series
High-cardinality metrics and event streams at line rate.
Vector
Embeddings, hybrid retrieval, and ANN search in the engine.
Full-text search
Text indexes alongside structured and vector data, no extra system.
Document
Native JSON ingestion, projection, and querying without schema drift.
Graph
Relationship traversal across entities, no separate graph engine.
Geospatial
Spatial indexes and predicates for location-aware workloads.
Key-value
Low-latency point reads and writes for state and cache patterns.
Streaming
In-flight processing alongside historical context, single query surface.
Seven systems and a glue layer, collapsed into one binary.
- Operational databasePostgres / MySQL
- Data warehouseSnowflake / BigQuery
- Time-series storeInfluxDB / Timescale
- Vector databasePinecone / Weaviate
- Search engineElastic / OpenSearch
- Stream processorKafka + Flink
- Glue layerETL · CDC · pipelines
- All nine workloads, one query surface
- Identity, policy, lineage at the kernel
- Vector and SQL share execution
- No pipeline glue, no embedding drift
- Same binary: cloud, on-prem, edge
Built for the AI-agent era, governed at the kernel.
The capabilities below are not optional add-ons. They are properties of the engine: simple to operate, AI-native by construction, sovereign by default, real-time over batch.
One unified data plane
Relational, time-series, vector, search, document, graph, geospatial, KV, and streaming converge into one query surface and one storage layer.
AI-native execution
Vector search, hybrid retrieval, and live inference run inside the engine. No sidecar systems, no embedding drift, no glue services.
Single binary, zero ops
A C++ engine that runs the same on a laptop, a hyperscaler region, an air-gapped data center, or an industrial gateway. No cluster choreography.
Sovereignty by construction
Identity, policy, lineage, and residency are wired into every query before it executes. Audit-grade by default, not by audit project.
Real-time over batch
Streams, change data, and events processed in flight and served alongside historical context in millisecond budgets, not minutes.
Five layers, one binary.
AI execution surface
Vector search, hybrid retrieval, model serving, and agent state. All share the engine and policy plane.
Governance kernel
Identity, policy, lineage, and residency enforced before any query runs. Audit-grade by default.
Unified query plane
One SQL surface across relational, vector, time-series, search, document, graph, geo, KV, and streams.
Real-time + historical fabric
In-flight stream processing alongside historical context. No batch-first compromise.
Single-binary C++ engine
High-performance core. ARM and x86. Cloud, on-prem, edge. Same binary, same semantics.
We retired four systems and a CDC layer in one quarter. The same engine now serves our analytics, vector search, and operational queries. Latency dropped, on-call burden dropped, cost dropped.
- 5×Systems retired in a single migration window
- 70%Reduction in pipeline glue and ETL
- <5 msP99 query latency at production scale
- SOC 2 Type II
- ISO 27001
- GDPR
- HIPAA
- PCI DSS
- Air-gapped
- ARM + x86
- On-prem · Cloud · Edge
One engine. Every workload. Yours to run.
Ver cómo MonkDB puede unificar su infraestructura de datos, con cero compromisos en soberanía, rendimiento o escala.
Reserva una demostración