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MonkDB is an AI native Operational Intelligence engine
MonkDB is an AI-native Operational Intelligence Engine that unifies and operationalizes enterprise data across IT and OT environments. It seamlessly connects to diverse endpoints, protocols, data types, and streaming sources, creating a real-time intelligence layer that breaks down silos and accelerates AI, analytics, and automation initiatives. By contextualizing high-velocity operational data at scale, MonkDB transforms fragmented information into actionable insights, predictive intelligence, and autonomous decision-making. From edge to cloud, it empowers enterprises to build resilient, adaptive, and data-driven operations with unmatched speed, visibility, and intelligence.
MonkDB facilitates unifying timeseries, geospatial, graph, vector, fulltext search, relational, and JSON workloads into MonkDB, a unified engine fronted by a SQL API. This allows teams to optimize infra and remove fragmented bottlenecks.
MonkDB's efficient indexing allows data to be streamed continuously from diverse sources based on different protocols in real time without the tax of re-indexing and putting pressure on underlying resources. It ensures data keeps evolving instead of reindexing each time when a record is written.
MonkDB's execution is based on distributed execution across nodes for massive concurrent reads and writes. Its storage engine is based on columnar strategy to ensure support for massive scale with efficient handling.
AI-Native Built-In enables organizations to create rich, multi-dimensional context for AI systems by combining vector embeddings for semantic understanding, full-text keyword search for precision retrieval, and graph relationships to uncover contextual connections. It further enriches intelligence with JSON-based metadata, geospatial data for location-aware insights, and time-series information for temporal context. This unified approach empowers AI applications with deeper understanding, more accurate retrieval, robust reasoning, and context-aware inference, enabling smarter decisions and higher-quality outcomes across complex enterprise environments.
In-Built Data Lineage provides end-to-end visibility into the complete lifecycle of enterprise data using SQL-native lineage tracking. It automatically captures where data originates, how it is transformed, enriched, and processed, and where it is ultimately consumed or stored. By mapping data flows across systems, pipelines, and applications, MonkDB enables organizations to understand data dependencies, improve governance, accelerate troubleshooting, ensure compliance, and build greater trust in AI and analytics outcomes through complete data transparency and traceability.
Native Governance, Policies, and Audit delivers enterprise-grade control, security, and accountability across the entire data and AI lifecycle. MonkDB enables organizations to define and enforce fine-grained governance policies, access controls, and compliance rules at scale. Comprehensive auditing capabilities provide complete visibility into data access, modifications, system activities, and policy enforcement, ensuring transparency and traceability. With built-in governance and continuous monitoring, organizations can confidently meet regulatory requirements, strengthen security posture, mitigate risk, and maintain trust in mission-critical AI, analytics, and operational workloads.
Red Hat certified products are tested to meet Red Hat’s criteria and supported as defined in the Red Hat Collaborative Support Process.
Partner validated products are tested by Red Hat Partners and supported as defined in the Red Hat Third Party Component Policy.
MonkDB is an AI-native operational intelligence platform that combines relational, document, graph, vector, geospatial, time-series, and governance capabilities within a single distributed engine. Unlike traditional databases that require multiple specialized systems, MonkDB enables organizations to store, search, analyze, govern, and operationalize data across diverse workloads using a PostgreSQL-compatible SQL interface. This unified architecture reduces complexity, eliminates data silos, and accelerates AI and analytics initiatives
MonkDB provides native governance controls including row-level filtering, column masking, policy management, contracts, validation rules, auditing, lineage tracking, and AI usage policies. These capabilities help organizations enforce compliance requirements, protect sensitive information, establish accountability, and maintain trust across AI, analytics, and operational workloads without relying on external governance tools
Yes. MonkDB supports PostgreSQL-compatible connectivity through PGWire and includes Foreign Data Wrapper (FDW) capabilities for external systems such as JDBC and Iceberg sources. It can connect with enterprise applications, analytics platforms, data lakes, streaming systems, and operational technologies, enabling organizations to create a unified intelligence layer without extensive data migration efforts.
MonkDB is designed as a distributed platform with clustering, scaling, replication, snapshot management, restore capabilities, monitoring, diagnostics, and production deployment support. It can be deployed across multi-node environments, Kubernetes platforms, or enterprise infrastructure, providing high availability, resiliency, and operational continuity for mission-critical workloads.