EnterpriseDB (EDB) has unveiled its latest product, EDB Postgres AI, a powerful solution that integrates a PostgreSQL database with a data lakehouse, tailored to support a wide range of workloads including transactional, analytical, and AI-driven tasks.
An Evolution in Database Technology
On Thursday, EDB announced the launch of EDB Postgres AI, a sophisticated database system designed to handle not only traditional transactional and analytical workloads but also the demands of AI applications. Initially conceived as a data lakehouse under the codename Project Beacon, this product has since evolved into a comprehensive platform that merges EDB’s PostgreSQL technology with advanced data lakehouse capabilities.
The Growing Influence of PostgreSQL
PostgreSQL, known for its object-relational database model, has been steadily gaining traction in the industry. Its open-source nature and adaptability across various workloads make it a preferred choice for many enterprises. According to Matt Aslett, Director at ISG’s Ventana Research, PostgreSQL’s versatility makes it an ideal solution for both transactional and analytical needs.
PostgreSQL’s expanding ecosystem, bolstered by a multitude of database providers, has established it as a leading open-source database in the enterprise space. DB-Engines’ data reflects this growth, ranking PostgreSQL as the fourth most popular RDBMS and overall database product.
Competition and Market Position
The increasing popularity of PostgreSQL has prompted major cloud providers like AWS, Google Cloud Platform, and Microsoft Azure to offer database services built on this technology. Notable examples include Amazon Aurora, AlloyDB, CitiusDB, and Amazon RDS for PostgreSQL. EDB faces competition from other PostgreSQL-based solutions such as YugabyteDB and CockroachDB.
Key Features of EDB Postgres AI
EDB describes its new platform as an “intelligent data platform” that offers a centralized management console, Postgres databases, lakehouse analytics, and AI/ML capabilities, including vector database support.
The management console provides a unified interface for overseeing all EDB Postgres AI operations, enhancing the visibility and control of an enterprise’s database infrastructure. It also features an AI agent to assist in managing on-premises databases.
EDB Postgres AI supports a wide array of databases, including EDB Postgres Advanced Server and its high-availability versions, which offer compatibility with Oracle Database. The lakehouse analytics component integrates both structured and unstructured data through the use of Nodes, which accommodate various data formats.
The AI/ML component, featuring vector database support, enables the creation of AI-driven applications. Additionally, the platform supports a variety of extensions such as Postgres Enterprise Manager, Barman, Query Advisor, and migration tools like the Migration Toolkit and Migration Portal. The latter is particularly notable for its embedded AI copilot, which aids in crafting migration strategies.
Enhanced Capabilities and Strategic Partnerships
EDB Postgres AI’s key strengths include rapid analytics, enhanced observability, vector support, high availability, and modernization of legacy systems. The platform enables enterprises to quickly deploy analytics clusters and optimize operational data storage for fast analysis.
The acquisition of Splitgraph, a startup known for its PostgreSQL-compatible serverless SQL API, has been instrumental in developing EDB’s advanced analytics capabilities. EDB’s recent partnerships with Red Hat, Nutanix, and SADA further extend the platform’s functionality. For instance, the collaboration with Red Hat allows enterprises to build AI models on Red Hat OpenShift AI and leverage EDB Postgres AI for enterprise-grade operations.
