PostgreSQL Archives

Tech Optimizer

June 11, 2026

As the Agentic Era Reshapes the Data Layer, Enterprises Build Their Sovereign Foundation on EDB Postgres® AI

EnterpriseDB (EDB) has reported a significant increase in global adoption of its EDB Postgres® AI (EDB PG AI) platform, indicating a trend among enterprises to standardize operations on a robust platform for managing mission-critical workloads. Research by MIT Technology Review Insights, in collaboration with EDB, shows that AI and data sovereignty are critical predictors of success in AI initiatives, with organizations prioritizing control over their data achieving a fivefold return on investment. The Industrial Bank of Korea (IBK) transitioned 15 core systems to EDB PG AI for greater operational flexibility and cost efficiency, reducing licensing costs compared to Oracle. Shinhan EZ Insurance migrated its entire core system to the public cloud to ensure uninterrupted service. Other enterprises leveraging EDB PG AI include MNTN, Euronext FX, and Kyobo Book Centre, which have benefited from enhanced stability, reduced vendor risk, and improved compliance. EDB is recognized as a leader in the field and will host a global digital event titled "The Era of Agentic AI Data" on June 25. EDB Postgres® AI is positioned as an open, enterprise-grade sovereign data and AI platform, supporting secure, compliant, and scalable solutions across various environments.

Tech Optimizer

June 10, 2026

Microsoft Open-Sources PostgreSQL Extension for In-Database Durable Execution

Microsoft has introduced pg_durable, a PostgreSQL extension that enables developers to execute durable workflows within the database, reducing the need for external orchestration systems. It simplifies workflow management by allowing developers to express long-running, fault-tolerant SQL functions directly in SQL, managing execution concerns like retries and recovery. Workflows are defined in SQL, with the extension handling retry states, progress tracking, and checkpointing. A pg_durable function operates as a graph of SQL steps that can resume from the last durable checkpoint after a failure. The extension preserves execution states within PostgreSQL tables, ensuring workflows can withstand crashes and restarts. It includes a domain-specific language (DSL) for scheduling and parallel execution. An example of a durable function is provided, demonstrating sequential and parallel execution using specific operators. pg_durable is particularly useful for vector embedding pipelines and scheduled maintenance tasks. Architecturally, it consists of a PostgreSQL extension and a background worker built on Rust libraries, without any external control plane. Durable execution allows long-running workflows to automatically resume from failure points, simplifying distributed system architecture.

Tech Optimizer

June 10, 2026

Tiger Data launches Ghost managed PostgreSQL service for AI agents

Tiger Data has launched Ghost, a managed PostgreSQL service designed for AI agents, providing infrastructure for coding and workflow agents to conduct large-scale experiments. The service features Fluid Storage, which uses a copy-on-write methodology to optimize storage efficiency and reduce costs by charging users only for modified data. Ghost also includes a "fast forking" capability, allowing users to quickly duplicate datasets for experimental environments. It is compatible with major PostgreSQL extensions like TimescaleDB and PostGIS. The pricing model is usage-based, charging users based on actual computing consumption rather than the number of databases created.

Tech Optimizer

June 9, 2026

Tiger Data launches PostgreSQL extension designed for AI agents

Tiger Data has launched a managed PostgreSQL database service called Ghost, designed for AI agents, addressing the limitations of traditional database architectures for autonomous software. The service is now generally available and allows agents to create unlimited databases quickly through a feature called "fast forking." Ghost utilizes Tiger Data's Fluid Storage technology, which employs a copy-on-write storage layer, enabling multiple database instances to share data blocks while charging users only for changed data. The service supports popular PostgreSQL extensions and is positioned as an evolution of PostgreSQL, maintaining its compatibility with the existing ecosystem. Tiger Data has raised 0 million in funding and employs 200 individuals across 25 countries.

Tech Optimizer

June 9, 2026

Tiger Data Launches Ghost, a Purpose-Built Database Service for the Agentic Era

Tiger Data has launched Ghost, a database service designed specifically for AI agents, addressing the limitations of traditional databases in supporting AI-driven workflows. Ghost allows for isolated environments where agents can experiment without affecting shared resources, offering unlimited Postgres databases with rapid forking capabilities. It features a cost-effective per-query pricing model and includes a free tier with 100 compute hours per month and 1TB of storage. Ghost is compatible with various MCP-enabled agent harnesses and is built on Postgres, providing a familiar operational model for teams. Comprehensive documentation and deployment resources are available at tigerdata.com.

Tech Optimizer

June 8, 2026

Pentasystem partners with EDB to target sovereign AI with EDB PostgreSQL database

Pentasystem Technology has partnered with EDB to enhance enterprise-grade data management using the EDB PostgreSQL database. This partnership, announced on June 8, aims to provide cost-effective and stable database solutions amidst rising costs from existing database management systems. Pentasystem plans to explore projects related to cloud computing, artificial intelligence, and data warehousing, focusing on creating a comprehensive integrated data platform. Jong-jun Jang, CEO of Pentasystem, noted the synergy between EDB's technology and Pentasystem's implementation expertise, aiming to deliver improved performance and cost savings to clients in various sectors.

Tech Optimizer

June 7, 2026

Implementing real-time change data capture with Debezium for Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL

Amazon Aurora PostgreSQL-Compatible Edition and Amazon RDS for PostgreSQL now support native streaming replication, allowing data changes to flow from source databases. Organizations often struggle to capture and propagate these changes in real time without affecting database performance. Traditional ETL pipelines can introduce significant delays, leading to outdated data and missed opportunities. Debezium is an open-source platform for change data capture (CDC) that monitors databases and streams changes to applications or data pipelines, enabling real-time data synchronization. The CDC solution combines PostgreSQL's logical replication with Debezium's change capture framework, focusing on Amazon Aurora for PostgreSQL. To implement this solution, logical replication must be enabled on Amazon Aurora through DB cluster parameter groups. Debezium connectors monitor the database's Write-Ahead Logging (WAL) via logical replication slots, converting transaction logs into structured event streams. Key components of the solution include: - Amazon Aurora for PostgreSQL as the source database with logical replication enabled. - A Debezium PostgreSQL connector running on MSK Connect for change capture. - Amazon MSK for message streaming. - An Amazon EC2 instance for testing and consuming change events. Steps to implement the solution include: 1. Creating an Amazon Aurora for PostgreSQL DB cluster and enabling logical replication. 2. Creating an Amazon MSK serverless cluster. 3. Setting up an Amazon EC2 instance to install Kafka and connect to the database. 4. Creating a custom plugin for Amazon MSK to replicate changes from RDS for PostgreSQL. 5. Uploading the custom plugin to an Amazon S3 bucket. 6. Storing credentials in AWS Secrets Manager and creating an IAM role for MSK Connect. 7. Testing the solution by verifying data replication and monitoring real-time changes. Monitoring can be done through CloudWatch Logs and the MSK Connect console, addressing common issues like replication slot lag and connector failures. To avoid charges, resources created during the implementation should be deleted in the correct order.

Tech Optimizer

June 6, 2026

PostgreSQL Dump and Restore: The Complete pg_dump Guide

pg_dump is a utility for exporting a PostgreSQL database into a file, which can be restored on the same or different servers. It exports a single database's tables, views, sequences, functions, indexes, triggers, and in-database grants but does not include roles, tablespaces, or server-level configurations. To capture global objects, pg_dumpall --globals-only should be executed prior to the per-database dump. pg_dump requires CONNECT and SELECT privileges on all tables and sequences within the target database, and a dedicated backup role is sufficient for single-database dumps, while superuser access is needed for global objects. pg_dump supports various output formats: plain SQL (.sql), custom binary (.dump), directory of files, and tar archive (.tar), each with different capabilities for restoration and compression. The custom format allows for selective and parallel restoration. For non-interactive use, credentials can be stored in a .pgpass file or passed via the PGPASSWORD environment variable. Restoration methods depend on the dump format: psql is used for plain SQL files, while pg_restore is used for custom and directory formats. The restoration process requires the target database to be created beforehand. Version mismatches between pg_dump and pg_restore can lead to failures, so it's essential to ensure that the binaries are version-matched. In Docker, pg_dump and pg_restore can be executed within containers, but care must be taken to manage credentials and ensure version compatibility. Exit codes from pg_dump should be checked to confirm successful operations.

Tech Optimizer

June 6, 2026

Implementing real-time change data capture with Debezium for Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL

Amazon Aurora PostgreSQL-Compatible Edition and Amazon RDS for PostgreSQL support native streaming replication, allowing data changes to flow from source databases. Organizations often struggle with real-time data capture and dissemination, leading to outdated information due to traditional batch ETL pipelines. Debezium is an open-source platform for change data capture (CDC) that streams database changes to applications or data pipelines in real time. The CDC solution utilizes PostgreSQL's logical replication capabilities and Debezium's framework. Key components include Amazon Aurora for PostgreSQL as the source database, a Debezium PostgreSQL connector on MSK Connect, Amazon MSK for message streaming, and an Amazon EC2 instance for testing. To implement the solution, users must enable logical replication on Amazon Aurora, create an Amazon MSK cluster, set up an EC2 instance with Kafka, and create a custom plugin for MSK Connect. The process involves configuring IAM roles and policies, connecting to the database, and creating an Amazon MSK connector to stream changes. Testing the solution includes verifying real-time changes by inserting, updating, and deleting records in PostgreSQL, with events appearing in Kafka. Monitoring tools are available through CloudWatch for troubleshooting issues like replication slot lag and connector failures. To clean up resources after testing, users should delete the MSK Connect connector, custom plugin, Amazon MSK cluster, Aurora PostgreSQL database instance, EC2 instance, IAM role and policy, Secrets Manager secrets, CloudWatch Logs log group, and S3 bucket.

Tech Optimizer

June 6, 2026

Azure HorizonDB Enters Public Preview: Web IQ Already Powers Copilot and ChatGPT

Microsoft announced the public preview of Azure HorizonDB, a fully managed PostgreSQL-compatible database designed for agentic AI workloads, during Microsoft Build 2026 in San Francisco. HorizonDB features a "database-as-logs" architecture, allowing for sub-millisecond multi-zone commit latency and independent scaling of compute and storage. It incorporates a Rust-based storage engine, native DiskANN vector search, and in-database AI model invocation. Additionally, Microsoft launched Web IQ, a web-grounding API layer integrated into Microsoft Copilot and OpenAI's ChatGPT, which provides passage-level structured evidence objects rather than full documents. Web IQ is model-agnostic and aims to enhance information density and reduce costs. Both services are currently in limited availability, with HorizonDB open for preview signups across five Azure regions.