EDB Postgres AI Hybrid Manager#
EDB Postgres AI Hybrid Manager (HM) is the control plane of the EDB Postgres AI Platform—a sovereign AI, analytics, and Postgres management solution that runs anywhere you run Kubernetes. It offers a unified experience for deploying databases, running GenAI workloads, and scaling Postgres-native analytics across cloud, on-premises, or hybrid environments.
It is currently supported on the follow Kubernetes distributions for on-premises: Red Hat OpenShift (RHOS), Rancher RKE2, and for in-cloud: Amazon EKS, and Google GKE.
- Hybrid Manager Release Notes
- Known issues
- Multi-DC
- Core platform and resources
- Database cluster engine
- Incorrect database name displayed for EDB Postgres Distributed (PGD) clusters
- PGD-X cluster creation stuck in the “PGD - Reconcile application user” phase
- Failure to create 3-node PGD cluster when
max_connectionsis non-default - PGD database settings are not duplicated when creating or duplicating a second data group
- AHA Witness node resources are over-provisioned
- HA clusters use
verify-cainstead ofverify-fullfor streaming replication certificate authentication - Second node is too slow to join large HA clusters
- Backup and recovery
- AI Factory and model management
- HM console and observability
- EDB Postgres AI Hybrid Manager
- Installing Hybrid Manager
- Using Hybrid Manager
- AI Factory in Hybrid Manager
- Analytics in Hybrid Manager
- Sovereign Data and AI Factory
One platform, full control#
HM brings together the infrastructure, data, and application layers required to support modern Postgres-based data platforms:
Sovereign AI — Build and serve AI-powered workloads using your own infrastructure, with full control over GPU resources and GenAI pipelines.
Postgres-native analytics — Offload to open data formats like Iceberg and Delta Lake while preserving Postgres compatibility and control.
Operational excellence — Simplify backup, scaling, monitoring, and cluster lifecycle management for Postgres clusters.
Whether deployed in the cloud or on-premises, Hybrid Manager ensures observability, governance, and resilience across your data and AI stack.
What you can do#
Area |
Capabilities |
|---|---|
Database provisioning |
Deploy highly available PostgreSQL or Distributed Postgres clusters using the console, templates, or declarative manifests. |
AI integration |
Run sovereign GenAI pipelines , serve models with KServe, and build AI knowledge bases governed by your infrastructure. |
Analytics |
Offload cold data to Delta Lake or Iceberg , query with Postgres syntax, and enable hybrid transactional/analytical processing. |
Monitoring and observability |
Use the integrated dashboards that leverage Prometheus, Grafana, and Loki to obtain deep visibility into query health, resource usage, and system alerts. |
Security and access management |
Integrate with identity providers, define RBAC for projects and clusters, and manage secure access to your databases and services. |
Database migration |
Migrate schemas and data from external databases (Oracle, self-managed Postgres) to HM-managed clusters. Leverage integrated services for migration and schema assessment, data transfer (snapshot), and continuous replication (streaming) to achieve minimal downtime migrations. |
Start here#
Install Hybrid Manager on AWS EKS → Red Hat OpenShift (RHOS), Rancher RKE2, EKS, or GKE.
Sovereign Data and AI Factory (Hardware Appliance) → Sovereign Data and AI Factory hardware
Using Hybrid Manager → backup/restore, monitoring, migrations, cluster creation, multi-DC deployment and more
AI Factory Architecture on Hybrid Manager → sovereign GenAI pipelines, model serving, and retrieval systems
Analytics Concepts in Hybrid Manager → Delta Lake, Iceberg, tiered storage, and lakehouse patterns