MonkDB
AI-Native Unified Execution Platform

WhereDataBecomesAction

MonkDB is an AI-native unified execution platform that brings data, intelligence, and action into one system, so decisions happen in real time.

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VectorTime-SeriesGeospatialFull-Text SearchDocument / JSONStreaming SQLBlob StorageKey-ValueGraphIn-Memory LayerMulti-Modal AI
Positioning

From Data Systems to Execution Systems

Three shifts that turn fragmented stacks into one continuous operating plane.

01

Unify

All data in one engine. Vector, time-series, geospatial, document, blob, and streaming, on the same plane.

9 workloads, 1 engine
02

Understand

Live AI context built into the engine. Intelligence runs where the data lives, not after a pipeline hop.

Vector + hybrid retrieval
03

Act

Decisions trigger actions inside the system. No external orchestrators. No external delays.

In-engine triggers
Performance
LIVE
0.0M/sec
Writes sustained
Streaming ingest, single cluster
<0ms
p99 query latency
Vector and SQL in one plane
0
Workloads, one engine
Vector, time-series, geospatial, full-text, document, SQL, blob, key-value, graph
0.00%
Uptime SLA
Air-gapped deployments included
AI SolutionAI Services

Keep AI ecosystems grounded in continuous data context, connecting streams, databases, applications, and models into one secure layer.

Let us build the future of data infrastructure, together

Power AI ecosystems and agents with seamless access to real-time and historical data, through a single, unified query experience.

UserUser
20K+ Live Users

MonkDB is AI Ready

  • •Simple: single binary, zero ops
  • •Efficient: high-performance C++ engine
  • •Interoperable: every protocol and format
  • •Safe: sovereignty, governance, traceability
02 / About

Your complete data sovereignty, engineered for the AI-native era

0k
AI-Native Solutions
Delivered to Clients

The existing data infrastructure is excessively cumbersome, sluggish, and complex, making it unsuitable for constructing an AI-native sovereign Data Plane. MonkDB is prepared.

MonkDB unifies streams, databases, applications, and models into a single secure data layer, with built-in governance, identity, and policy enforcement. Every agent action is authorized and compliant before it is executed.

Governed AccessReal-Time StreamingFull TraceabilityAgent-Ready
Platform

The AI-Native Unified Execution Engine

MonkDB is a unified system where data is ingested, understood, and acted upon in real time. No pipelines, no delays, no fragmented tools.

  • Vector
  • Time-Series
  • Geospatial
  • Document
  • Blob
  • Streaming SQL
  • Full-Text
  • Key-Value
  • Graph

MonkDB consolidates vector, time-series, geospatial, document, blob, and streaming data into a single platform. It eliminates data movement and enables intelligence and execution directly where data resides, reducing latency and complexity.

TouchedVectorTime-SeriesGeospatialSQL
monkdb shell · productionLive
-- One query, four workloads, one engine
SELECT id, name,
  v.embedding <=> $query_vec AS similarity,
  ST_Distance(geo, $origin) AS distance_m,
  ts.value AS last_reading
FROM events e
JOIN vectors    v  ON v.event_id  = e.id
JOIN timeseries ts ON ts.event_id = e.id
WHERE ts.ts > now() - INTERVAL '1 minute'
  AND v.embedding <=> $query_vec < 0.30
ORDER BY similarity ASC LIMIT 25;
→ 25 rows  in  0.8 ms p99

No federation. No glue code. No data movement.

Difference

Most platforms stop at insight.MonkDB executes.

Traditional systems separate data, AI, and execution. MonkDB unifies them into a single system, enabling real-time intelligent operations without fragmentation.

01Unified by Design
ONE9 WORKLOADS1 ENGINE

All data types in one system

Vector, time-series, geospatial, document, blob, full-text, streaming SQL, key-value, graph. One engine. One query language.

02AI-Native Core

Intelligence built into the engine

Embeddings, vector search, hybrid retrieval, and live context, native to the data plane. No external AI layer to wire up.

03Execution Built-In
DECIDEACTIN-ENGINE LOOP

Instant action, not insight reports

Decisions trigger workflows, state updates, and downstream actions directly inside the engine. The loop closes here.

03 / Features

Why teams choose MonkDB

Keep architecture simple at scale

Most data stacks carry five systems doing the work of one, driving up ops cost and slowing teams. MonkDB collapses them into a single binary: fewer moving parts, cleaner SLOs, faster iteration.

Modern data strategy for an AI-agent world

Data now arrives from agents, workflows, and events in every format, at every cadence. MonkDB ingests, transforms, and serves it through a single query surface. No pipeline glue. No schema drift.

Real-time systems over static infrastructure

Autonomous systems produce data faster than batch can absorb. MonkDB processes streams in-flight and serves them alongside historical context. Decisions land in milliseconds, not minutes.

Self-governing infrastructure for AI workloads

AI workloads need infrastructure that governs itself. MonkDB ingests, processes, and stores at scale, with identity, policy, and lineage wired into every query before it executes.

Capabilities

Six engines, one system

MonkDB supports SQL, vector search, and real-time analytics in one execution layer, eliminating the need for multiple systems.

9 workloads

Multi-model engine

Nine workloads in one binary. Query across them with standard SQL.

VectorTime-SeriesGeospatialDocument
1 dialect

Hybrid query engine

Vector similarity, full-text search, time-series, and SQL filters in a single statement.

ANNBM25Spatial joinWindow fns
<1 ms write

Real-time ingestion

Streaming and batch ingestion, sub-millisecond write path, no separate broker required.

KafkaCDCS3 batchPulsar
C++ engine

High performance

Vectorized execution, native code paths, and a compact memory layout. Built in C++.

SIMDVectorizedARM + x86Zero-copy
SOC2 / ISO27001

Enterprise security

Identity, access, audit, and lineage built into every query before it executes.

RBACABACAudit logAES-256
ARM + x86_64

Flexible deployment

Cloud, on-premises, edge, or air-gapped. The same binary, the same semantics.

CloudOn-premEdgeAir-gapped
Stack

Replace complexity with one system

Replace databases, pipelines, vector DBs, and AI layers with a single unified platform.

MonkDB reduces infrastructure overhead, simplifies architecture, and accelerates time to production. Fewer systems to operate. Fewer integrations to babysit. Fewer moving parts in production.

Workload
Traditional Stack
MonkDB
Operational data
PostgreSQL, MySQL
Native
Vector search
Pinecone, Weaviate
Native
Time-series
InfluxDB, TimescaleDB
Native
Streaming SQL
Kafka + Flink
Native
Search and full-text
Elasticsearch, OpenSearch
Native
Geospatial
PostGIS, custom
Native
AI inference
vLLM, Triton, custom
Native
7 workloads
7+ vendors · 7+ ops surfaces
1 binary · 1 vendor
04 / Sovereignty

Your complete data sovereignty.
Secure and intact for an AI-first world.

The existing data infrastructure is excessively cumbersome, sluggish, and complex, which makes it unsuitable for constructing an AI-native sovereign data plane.

MonkDB is prepared.

  • Air-Gapped Ready
  • SOC 2 Type II
  • ISO 27001
  • GDPR
  • HIPAA
05 / Architecture

An AI-native sovereign data plane,
from streams to governance.

Four capabilities that together form the backbone of an AI-native data plane, designed to be operationally simple, governed by default, and always grounded in real-time context.

Diagram, Architecture
LIVE

Apps

IoT & Edge

Streams

PG Wire

MonkDB

Vector

Streaming SQL

Timeseries

Document/JSON

Geospatial

Full Text Search

Key-Value

Graph

In-Memory

Blob Store

Analytics

Search

AI Apps

& more

Flow

Data Sources to Action,
in one engine

MonkDB integrates ingestion, storage, compute, and execution into one distributed system.

Data Sources

Streams, databases, applications, sensors.

  • Kafka
  • S3
  • Postgres
  • OPC UA

MonkDB

Unified ingestion, storage, and query.

  • Multi-model
  • Vector
  • SQL

Intelligence

Vector search, hybrid retrieval, live context.

  • Embeddings
  • ANN
  • Hybrid

Execution

Decisions, triggers, workflows in-engine.

  • Triggers
  • Workflows
  • Webhooks

Applications

Apps, agents, dashboards, downstream systems.

  • Apps
  • Agents
  • BI
06 / Engine

MonkDB is beyond a database.

A database-only stack stitches together vector stores, time-series engines, stream processors, and document stores just to ship one feature. MonkDB replaces that stack with a single multi-model engine, the foundation of our AI-native sovereign data plane and the substrate for everything we build above it.

01 / Operating Layer

Monk AIO

AI-Native Operating Intelligence System

The operating layer that turns streaming data into autonomous decisions. Agents, orchestration, and real-time reasoning run natively on the sovereign data plane.

  • Autonomous
  • Real-time
  • Sovereign
02 / Platform Portfolio

SmartX Platforms

Domain and function-specific

Production platforms tuned to industry and operating function. SmartMine, SmartMobility, SmartFinance, and a growing portfolio, all powered by MonkDB and Monk AIO.

  • SmartMine
  • SmartMobility
  • SmartFinance
  • + more
MonkDB is AI ready
  • 01
    Simple

    Single binary, zero operational overhead.

    One process. One engine. No sidecars, no orchestrator sprawl, no glue code. Operations stay small as scale grows.

  • 02
    Efficient

    High-performance C++ engine with minimal footprint.

    Native code paths, vectorized execution, and compact memory layout. Designed to run the heaviest workloads on the smallest hardware you can give it.

  • 03
    Interoperable

    Built for every protocol, system, and data format.

    Speak SQL, stream events, ingest blobs, query vectors, serve documents. All from the same plane, with no pipeline glue in between.

  • 04
    Safe

    Data sovereignty, governance, and full traceability built in.

    Every action is authorized, every query is audited. Deploy on-prem, at the edge, or air-gapped, without ever giving up control of your data.

Proof, 4 modalities

Vector search, geospatial, time-series, and SQL, in a single statement. No pipeline, no glue, no federation.

Every workload compiles into the same plan. Joins happen natively, not across systems. The example below ranks nearby users by semantic similarity, filtered by live activity, in one query, at interactive latency.

monkdb · psqlSQL
 
 
 
 
 
 
 
 
 
 
 
 
 
VectorGeospatialTime-SeriesSQL
Performance

Built for the workloads that don't tolerate delay

Engineered in C++. Vectorized execution. Distributed by default. Production-tuned across the workloads that matter most.

0.0 ms
Sub-millisecond latency

p99 across vector, SQL, and streaming workloads.

p50p90p99
0×
Linear concurrency

Add nodes, get linear throughput. No coordinator bottleneck.

1×5×10×
0 PB+
Scalable architecture

Petabyte clusters. Cloud, on-prem, edge, air-gapped.

12-NODE CLUSTER
07 / Mission

AI transformed every aspect of enterprise data. Therefore, we constructed the platform they operate on.

The AI Native Sovereign Data Platform represents the answer from MonkDB to the era of AI and agency. It features a regulated access layer that integrates data systems to facilitate secure, contextual, and real-time AI.

07 / Comparison

How MonkDB compares,
feature by feature.

A side-by-side of the capabilities enterprise teams evaluate when consolidating onto a unified data plane. Sources: vendor documentation, public benchmarks, and customer deployments.

Deployment

Where it runs

MonkDB
Cloud, On-Prem, Edge

Processor

CPU architectures supported

MonkDB
ARM, x86_64

Multi-Model

V, TS, GIS, FTS, DOC, SQL, BLOB, KV, G

MonkDB
9 / 9

Hybrid Search

Vector and keyword in one query

MonkDB

HTAP

Transactional and analytical

MonkDB

AI-Native

Built-in embeddings, vector indexing, agent context

MonkDB

Sovereignty

Air-gapped, on-prem, zero egress

MonkDB

Licensing

Commercial model

MonkDB
Flexible EULAs
SupportedPartialNot supported

*Based on publicly available vendor documentation. Multi-model legend: V (Vector), TS (Timeseries), GIS (Geospatial), FTS (Full-Text), DOC (Document), SQL (Streaming SQL), BLOB (Blob), KV (Key-Value), G (Graph).

Use Cases

Production patterns running on MonkDB

Six places where unified execution replaces fragmented stacks. Click any card for the depth.

01

Digital Twins

Live system models that simulate, predict, and act in real time.

Real-time sync
02

AI Agents

Unified context plane for reasoning agents and copilots.

Live context
03

Fraud Detection

Anomalies caught and acted on as transactions clear.

<5 ms decision
04

Smart Manufacturing

Operational intelligence that predicts and corrects continuously.

Predictive ops
05

Smart Mobility

Dynamic routing and predictive coordination across fleets.

Dynamic routing
06

Financial Intelligence

Low-latency analytics, trading, and risk in one plane.

Trading-floor latency

Return on Investment with MonkDB

70%Cost reduction
5×Faster queries
1Unified platform

Key Differentiators

  • Multiple specialized databases
  • Complex, brittle data pipelines
  • Static infrastructure, no real-time
  • Increased DevOps overhead
  • Fragmented AI and governance

After MonkDB

  • Simple: single binary, zero ops
  • Efficient: high-performance C++ engine
  • Interoperable: every protocol and format
  • Safe: sovereignty and traceability built in
  • AI-ready: agent-grade context layer

Stop managing data. Start running systems.

Talk to an engineer. We will scope a proof of value in your environment.

Request Demo