Enterprise DB (EDB), a leader in Postgres data and AI solutions, has introduced several enhancements to EDB Postgres AI, enabling enterprises to develop secure, flexible, AI-powered applications in sovereign, hybrid environments.

Figure 1. EDB Postgres AI: Cloud Agility and Observability for Hybrid Environments.

According to EDB, the platform provides a unified interface, combining cloud agility with a hybrid-first intelligent architecture optimized for transactional, analytical, and AI workloads. This empowers organizations to accelerate AI adoption, from development to production-ready applications. Figure 1 shows EDB Postgres AI: Cloud Agility and Observability for Hybrid Environments.

Jozef de Vries, EDB's Chief Product Engineering Officer, emphasized the value of integrating AI solutions within existing systems that handle traditional operational workloads. He stated, “Our hybrid platform supports sovereign data workloads while offering cloud-like lifecycle management tailored to the customer’s environment. This simplifies data management across transactional, analytical, and AI workloads while delivering greater agility, portability, and precise control over total cost of ownership (TCO).”

EDB Postgres AI’s hybrid infrastructure supports modernization, cost management, and the demands of both traditional and AI-driven workloads. With features like simplified deployment, management, observability, and automation, it is designed as a versatile solution for transactional, analytical, and AI applications across any environment.

Key enhancements include:

1. Hybrid Control Plane:

A centralized management and real-time observability tool.

2. AI Accelerator:

A streamlined path from AI development to production-ready applications.

3. Analytics Accelerator

High-performance analytics across diverse data tiers.

The Hybrid Control Plane simplifies administrative tasks while delivering real-time observability in hybrid and multi-cloud environments. Available now in a tech preview, it enhances EDB Postgres AI Software Deployment.

The AI Accelerator, leveraging EDB’s Pipelines Extension and preloaded with pgvector, simplifies the integration of generative AI applications such as chatbots and recommendation systems within Postgres. It automates data pipelines for embedding generation, storage, indexing, and retrieval, reducing the need for extensive coding. Aislinn Wright, EDB's VP of Product Management, highlighted its capability to streamline the AI data lifecycle, enabling rapid transitions from experimentation to production.

The Analytics Accelerator integrates with lakehouse ecosystems and employs a Vectorized Query Engine to enable SQL-based queries on columnar data in external object storage. Its Tiered Tables functionality reduces complexity by offloading cold data to columnar tables, optimizing analytics across data tiers.

Additionally, PostgreSQL version 17 is now generally available across EDB’s product lineup, offering seamless workload management across self-hosted, private cloud, public cloud, and hybrid environments. These updates solidify Postgres as a high-performance platform for transactional, analytical, and AI workloads.

Source: Database

Cite this article:

Priyadharshini S (2024), "EDB Postgres AI Enhances Hybrid Environments with Cloud Agility and Observability", AnaTechMaz ,pp.113