EDB Previews Horizontal Scaling so Mission-Critical Postgres® Grows with Every Customer and Every Agent

As 86% of enterprise leaders expect an AI data system to be critical within three years, horizontal scaling gives the data layer room to grow, without sacrificing availability or control enterprises already trust.

WILMINGTON, Del., Oct. 29, 2026 /PRNewswire/ -- EnterpriseDB (EDB), the leading sovereign data and AI company, today announced a preview of horizontal scaling for EDB Postgres AI Distributed (PG AI Distributed). Planned for general availability in February 2027, the capability uses sharding to distribute transactional writes across node groups, expanding write capacity while retaining PG AI Distributed's established high-availability architecture. The preview advances EDB's vision for a sovereign AI data system for the agentic enterprise by strengthening the foundation that keeps autonomous work running at scale.

It arrives as enterprises consolidate fragmented data, AI, and agents into a single sovereign AI data system. That system runs mission-critical workloads that can never pause, such as payments gateway, core banking, high-ingest applications, and multi-tenant SaaS. Business growth shows up in the database. Every new customer and request add load, and now incoming AI agents working around the clock add more. Availability alone is insufficient when a system stays online but cannot keep pace, leaving agents unable to complete their work. Once writes reach a single server's limits, read replicas can't absorb them. Buying a larger machine adds cost and postpones the ceiling. Replacing the database turns growth into a migration project.

EDB is building a path beyond that ceiling within Postgres. Horizontal scaling spreads data and writes across shard groups that process work in parallel. Each group retains PG AI Distributed's replication, automatic failover, and configurable durability. Customers gain greater transactional capacity while preserving the availability practices, Postgres expertise, and infrastructure choice their business already relies on.

"An enterprise running its own AI data system needs control over how that system grows. A write ceiling should not force a database replacement or a retreat from the availability the business depends on. We're building the sovereign AI data system for the agentic enterprise. Horizontal scaling extends its operational foundation so customers can put more agents to work on the Postgres they already trust," said Max Romanenko, Chief Technology Officer, EDB.

More capacity. The same operational foundation.

Hitting a database limit can trigger months of work—buying more capacity, evaluating another platform, adapting applications, rebuilding availability protections, and retraining the team. EDB's approach extends the PG AI Distributed architecture those teams already operate: Shard groups are built the same way as the groups customers run today, with the same replication, failover, and durability mechanisms.

Built on systems where interruption has real consequences

PG AI Distributed already runs always-on systems for more than 75 financial institutions, backed by more than a decade of distributed Postgres engineering. Top banks globally rely on it for up to 99.999% availability across clouds, data centers, and air-gapped systems that run 24/7/365 and cannot tolerate downtime.

Its production footprint includes a 250-node cluster and a cluster managing more than 70 TB of transactional data. One customer operates more than 350 distributed clusters across over 10,000 cores.

Horizontal scaling builds on the replication, consensus, failover, and routing mechanisms behind those deployments. The preview extends that operational foundation to distributed writes, giving customers a path to greater capacity grounded in infrastructure already trusted with critical work.

Scaling out in PG AI Distributed works by adding groups, with the same runbooks, extensions, and in-place failover in seconds. Postgres stays Postgres, and quorum durability with asynchronous telemetry is set as policy for each workload, anywhere, with identical architecture on-premises, in the cloud, and hybrid.

The foundation for a sovereign AI data system

EDB's vision for the AI data system brings together multi-model data, governance at the data layer, agent runtime, and sovereign control. Horizontal scaling strengthens the transactional foundation beneath that system: the capacity to complete more work while retaining availability protections and control over where the platform runs.

For enterprises putting agents into continuous operation, that is a consequential shift. Growth can build on the systems and expertise they already trust, with more of their investment going toward the work they want to automate.

Availability

Horizontal scaling is in preview with customer design partners, with general availability planned for February 2027. The initial release is designed around transactions that operate within a shard group.

Read the technical blog and watch the demo preview.

About EDB

EDB Postgres® AI (EDB PG AI) is the sovereign AI data system for the agentic enterprise. Built on Postgres, the world's leading open source database, EDB PG AI unifies transactional, analytical, and AI workloads in a single architecture, eliminating the data movement, ETL, and operational fragmentation that slow enterprises down. With governance enforced at the data layer and the flexibility to deploy on-premises, in hybrid environments, or across clouds, enterprises operationalize their data and AI on infrastructure they own and control—reaching production-ready sovereign AI in weeks, not months. As one of the most active contributors to the PostgreSQL project, EDB is deeply invested in the vitality of the global open source community. To learn more, visit www.enterprisedb.com.

EnterpriseDB and EDB are registered trademarks of EnterpriseDB Corporation. Postgres and PostgreSQL are registered trademarks of the PostgreSQL Community Association of Canada and used with their permission. All other trademarks are owned by their respective owners.

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SOURCE EnterpriseDB