EnterpriseDB targets AI development with latest update
A low-code/no-code interface and data observability across hybrid environments address the challenges enterprises face moving AI projects beyond development and into production.
EnterpriseDB on Tuesday introduced new features for its EDB Postgres AI platform aimed at simplifying the development and management of AI applications.
Included are a low-code/no-code environment for developing applications and data observability across hundreds of databases on-premises and in the cloud to address data quality.
First launched in May 2024, EDB Postgres AI is a unified database platform for managing transactional, analytical and AI workloads. In addition, it unifies relational and nonrelational data, features automated data pipelines, and includes application development tools.
Historically, enterprises have struggled to move AI initiatives beyond development and into production, with the failure rate of AI projects estimated to be around 80%. Given that EnterpriseDB's new capabilities address the likelihood of an AI project reaching production by simplifying building and managing AI development systems, they are valuable additions, according to Stephen Catanzano, an analyst at Enterprise Strategy Group, now part of Omdia.
The latest EnterpriseDB update is significant for users as it introduces industry-first advancements to the Postgres AI platform that enable secure, agentic, sovereign DevOps across Postgres estates.
Stephen CatanzanoAnalyst, Enterprise Strategy Group
"The latest EnterpriseDB update is significant for users as it introduces industry-first advancements to the Postgres AI platform that enable secure, agentic, sovereign DevOps across Postgres estates," he said. "This update is particularly valuable because [few] enterprises have successfully deployed agentic AI at scale."
Based in Wilmington, Del., EnterpriseDB is a database specialist whose capabilities are built on the open source PostgreSQL format. Competitors include database specialists such as MongoDB and MariaDB, as well as tech giants providing PostgreSQL options, including AWS, Google, Microsoft and Oracle.
New capabilities
Like many data management vendors, EnterpriseDB is creating an environment for AI development in response to rising interest from enterprises in using proprietary data to build applications that understand the unique characteristics of their operations.
EnterpriseDB, however, has a built-in advantage over some data management vendors expanding into AI development because its platform is built on PostgreSQL, Catanzano said.
Now the most popular database, PostgreSQL is gaining momentum as a platform for enabling AI development due to its flexibility and versatility. PostgreSQL not only supports both analytical as well as transactional workloads, but also geospatial, time series, JSON and vector database workloads that enable the discovery of unstructured data.
Recently, Databricks and Snowflake each acquired PostgreSQL database vendors to add to their AI development capabilities.
"In the past months there has been a big uptick in news around Postgres, which is very good for [EnterpriseDB]," Catanzano said. "It's mostly about the flexibility of Postgres as a platform for AI and ties in to the move to unlock unstructured data, [which gets] organized by Postgres."
Matt Aslett, an analyst at ISG Software Research, likewise noted that with PostgreSQL gaining popularity as a foundation for AI development, EnterpriseDB's new capabilities are important additions for a vendor that is well known in the PostgreSQL community, but doesn't have as high a general profile as many of its competitors.
"EnterpriseDB is well placed to take advantage of increased adoption of PostgreSQL as well as widespread interest in agentic AI," he said.
As a result, the new capabilities are important additions, furthering the vendor's AI development capabilities within a PostgreSQL environment, Aslett continued.
"The latest release is significant in providing a low-code environment for creating AI-driven applications, as well as management and monitoring for an enterprise PostgreSQL estate across a hybrid combination of cloud and on-premises deployments," he said.
The low-code/no-code capabilities provide a point-and-click interface combined with an SDK that enables EnterpriseDB users to set up AI pipelines with just five lines of code. In addition, an integration with Nvidia NIM provides GPUs that deliver processing performance and a microservices architecture to run models locally and ensure data security.
Meanwhile, new hybrid management capabilities include data observability across hundreds of PostgreSQL databases irrespective of the hosting environment. Hybrid management provides users with more than 200 built-in metrics that are automatically observed and recommends fixes for any issues it detects.
In addition, EnterpriseDB added transparent data encryption to improve data security, a new analytics engine optimized for AI workloads that includes support for Apache Iceberg and Delta tables, and a universal operational data store that enables users to develop applications with disparate data types, including structured and unstructured data.
All of the additions were motivated by customer feedback, according to Jozef de Vries, EnterpriseDB's chief product engineering officer.
"These were answers to the practical limits our customers kept hitting," he said. "They wanted to get more value out of the data already in their Postgres systems -- analyze it in place, secure it and use it in GenAI workflows. We added what they needed to do that."
Looking ahead
With its latest additions, EnterpriseDB now has its foundation for AI development in place, according to de Vries.
Next, the vendor's focus will be on scale and performance, which numerous database vendors, including Aerospike and Oracle, are also addressing, he said. In addition, EnterpriseDB plans to add more integrations through partnerships to broaden its AI ecosystem.
That focus on partnerships is wise, according to Catanzano.
"Expanding their partner ecosystem beyond current collaborations with Red Hat and Supermicro could help them reach new markets and customer segments," he said.
In addition, opportunities to grow beyond its PostgreSQL database roots include adding more industry-specific tools, providing autonomous agentic AI tools within the EnterpriseDB platform to take on maintenance tasks, improving multi-cloud capabilities to provide a more seamless experience across environments and providing a more comprehensive data governance suite, Catanzano continued.
Aslett, meanwhile, suggested that EnterpriseDB do more to increase its visibility. Founded in 2004, EnterpriseDB has raised $67.9 million in funding. Other, much more recently founded database vendors such as SingleStore and MongoDB have raised far more and are better known.
"While the company is well known in the PostgreSQL community, it could raise its profile to better enable it to compete with the various industry heavyweights that dominate the wider market," Aslett said.
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.
