Deploy and manage enterprise PostgreSQL databases on private cloud with automated lifecycle management and vector database support for AI. Tanzu for Postgres provides a complete Postgres distribution with high availability, Transparent Data Encryption, and pgvector for RAG workflows.
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PostgreSQL is one of the most capable open source databases available, with a diverse ecosystem of extensions covering everything from geospatial data to vector search. But running Postgres at enterprise scale requires automated operations, hardened security, and expert support. Tanzu for Postgres delivers all of this on infrastructure you control.
A centralized Postgres operator manages the full lifecycle of every database instance. Deployment, failover, scaling, and fleet-wide operations are automated across your entire Postgres environment.
All major versions are supported during the 5-year support lifecycle of Postgres releases, so teams can lock in a version without worrying about rapid changes.
Tanzu for Postgres Advanced includes Transparent Data Encryption (TDE), providing data-at-rest protection for sensitive information. Security auditing capabilities and enterprise-hardened packaging meet compliance requirements.
High availability with automated failover, read replicas, and multi-data center management keeps databases resilient.
Use pgvector to store and query embedding vectors alongside relational data. Enable retrieval-augmented generation (RAG) workflows for AI applications without deploying a separate vector database.
Keep AI data on private infrastructure for organizations that need control over data used in LLM-powered applications.
Manage your entire PostgreSQL fleet from a centralized operator on Kubernetes. Routine operations like deployment, failover, and scaling are automated cluster-wide.
On-demand self-service provisioning through Tanzu Platform lets developers create and manage Postgres instances without waiting on DBA teams.
Store embedding vectors directly in PostgreSQL using pgvector. Enable fast vector similarity search for retrieval-augmented generation, recommendation engines, and semantic search applications.
Combine vector search with traditional SQL queries in a single database, eliminating the need for a separate vector database in your AI architecture.
Deploy on Kubernetes, virtual machines, public cloud, or bare metal. RPM packages include the core Postgres engine and community packages hardened for the enterprise.
Packages available for Tanzu Platform, Tanzu Kubernetes, or standalone RPM deployment to match your infrastructure model.
AI teams building retrieval-augmented generation (RAG) workflows need a vector database to store and query embedding vectors. Many organizations prefer to keep this data on private infrastructure rather than sending it to cloud vector database services.
Tanzu for Postgres with pgvector enables fast vector similarity search alongside traditional relational queries. Teams can store embeddings, documents, and metadata in a single database, simplifying the AI data architecture.
Organizations running PostgreSQL on Amazon RDS, Azure Database for PostgreSQL, or Google Cloud SQL often face escalating costs and limited control over their database infrastructure. Moving back to private infrastructure requires equivalent automation.
Tanzu for Postgres provides the same automated provisioning, failover, backup, and scaling capabilities as cloud-managed services. Teams get the cloud-like experience on infrastructure they control, with full data sovereignty.
PostgreSQL is increasingly chosen as the primary database for enterprise applications due to its extensibility, standards compliance, and diverse ecosystem. Organizations need a production-grade Postgres platform that scales with their application portfolio.
Tanzu for Postgres provides fleet-wide management, automated failover, backup and recovery, and security auditing. Platform engineers can offer developers self-service Postgres provisioning while maintaining enterprise governance.
Tanzu for Postgres is an enterprise-grade PostgreSQL distribution that supports deployment on Kubernetes, virtual machines, public cloud, or bare metal. It includes automated lifecycle management, high availability, backup and recovery, and Transparent Data Encryption.
The VMware Tanzu team has a 20-year heritage in the Postgres community through their involvement in Greenplum Database and contributions to core PostgreSQL development.
Yes. Tanzu for Postgres includes pgvector support for fast vector similarity search. This enables retrieval-augmented generation (RAG) workflows, recommendation engines, and semantic search applications.
Organizations can store embedding vectors alongside relational data in a single database, simplifying their AI data architecture without deploying a separate vector database.
Yes. Organizations migrating from cloud-managed PostgreSQL services like Amazon RDS or Azure Database for PostgreSQL can use Tanzu for Postgres on private infrastructure with comparable automation.
It provides automated provisioning, failover, scaling, backup, and recovery with full control over data residency and infrastructure costs.
Tanzu for Postgres Advanced includes Transparent Data Encryption (TDE) for data-at-rest protection. It also provides security auditing, enterprise-hardened packaging with timely patches, and high availability with automated failover.
Additional capabilities include read replicas, multi-data center management, and backup and recovery from a curated collection of best-of-breed open source components.
VirtualizationWorks helps organizations evaluate Tanzu for Postgres for their application and AI database needs, plan migration from cloud services, and understand licensing options.
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