PostgreSQL Archives

Tech Optimizer

April 12, 2026

Modernizing Nexus Repository: Moving Beyond OrientDB

Support for OrientDB in Sonatype Nexus Repository has been discontinued, and older versions of Nexus Repository (prior to 3.70.5) are built on an outdated architecture that presents high-severity vulnerabilities and cannot be fully patched. The recommended database for Nexus Repository is now PostgreSQL, which offers better performance and support for modern architectures. Users have two migration options: transition to Sonatype Nexus Repository Cloud, which is fully managed and eliminates database management, or migrate to PostgreSQL while maintaining a self-hosted environment, which requires ongoing maintenance and infrastructure ownership.

Tech Optimizer

April 11, 2026

Overcoming barriers to database modernisation in the AI age

Enterprises in Malaysia are transitioning from legacy systems to modern infrastructure to facilitate AI deployment. A roundtable discussion highlighted the challenges of AI integration, emphasizing the need to reduce costs associated with outdated systems. Organizations are adopting hybrid cloud approaches and utilizing various databases to manage extensive data across multiple applications. The push for AI is driven by management and customer expectations, but employee willingness to upskill remains a challenge. Not all challenges require AI solutions, and starting with smaller use cases can lead to successful scaling. The adoption of open-source database systems like Postgres is increasing, necessitating reliable support to address issues and ensure application availability. Data sovereignty is a concern for enterprises operating in mixed environments, and EDB Postgres AI offers a platform that combines security with cloud agility. Reducing infrastructure costs is essential for freeing up resources for new initiatives.

Tech Optimizer

April 11, 2026

Google Cloud Highlights Ongoing Work on PostgreSQL Core Capabilities

Google Cloud has made technical contributions to PostgreSQL, focusing on advancements in logical replication, upgrade processes, and system stability. Key developments include the evolution of logical replication towards active-active configurations with automatic conflict detection to identify row-level conflicts during replication. This progress has sparked discussions about consistency models in database systems. Enhancements have also expanded logical replication to include sequences, reducing manual synchronization needs. Improvements to pg_upgrade have streamlined large object management and reduced upgrade times, while ensuring WAL data retention and schema constraint preservation. Bug fixes have addressed issues with index pages, extension loading, and WAL flush logic. Future features under development include a structured conflict log for replication and enhancements to parallel data export in pg_dump.

Tech Optimizer

April 11, 2026

Database Branching in Postgres: Git-Style Workflows with Databricks Lakebase

Database branching is a modern approach that addresses the limitations of traditional database management in development workflows. Unlike conventional database copies, which require significant time and resources to duplicate data and schema, database branching allows for the creation of isolated environments that share the same underlying storage. This method utilizes a copy-on-write mechanism, enabling branches to be created in seconds regardless of database size, with storage costs tied only to the changes made. Key features of database branching include: - Branch creation time: Seconds, constant regardless of database size. - Storage cost: Proportional to changes only, not the total data size. - Isolation: Each branch has its own Postgres connection string and compute endpoint. - Automatic scaling: Idle branches can scale compute to zero, incurring costs only when active. The architecture supporting this approach separates compute from storage, allowing multiple branches to reference the same data without conflict. This design facilitates time travel capabilities, enabling branches to be created from any point in the past for instant recovery and inspection. Database branching unlocks new workflows, such as: - One branch per developer, providing isolated environments for each engineer. - One branch per pull request, automating branch creation and deletion tied to PRs. - One branch per test run, provisioning fresh databases for each CI pipeline execution. - Instant recovery from any point in time within a designated restore window. - Ephemeral environments for AI agents, allowing programmatic database provisioning. Databricks Lakebase offers this database branching capability, transforming the database from a bottleneck into a streamlined component of the development process.

Tech Optimizer

April 8, 2026

True enterprise sovereignty is more approachable than ever, thanks to K8s-powered cloud-neutral PostgreSQL

Discussions on digital sovereignty are shifting from infrastructure to databases, driven by geopolitical pressures in Europe. Hyperscalers like Amazon and Microsoft are investing heavily to comply with new regulations, prompting organizations to reconsider their reliance on managed cloud services. Many enterprises are now viewing PostgreSQL as a portable, cloud-neutral foundation to ensure consistent behavior across various environments, leading to interest in Sovereign DBaaS. Gabriele Bartolini, VP and Chief Architect of Kubernetes at EDB, emphasizes that true sovereignty starts with the database and that portability enhances negotiating leverage and compliance. Bartolini warns that while managed cloud services offer convenience, they often sacrifice control. He notes that transitioning away from these services can provide long-term leverage, as evidenced by Microsoft's encouragement for customers to run self-managed PostgreSQL. The Operator Pattern in Kubernetes enables better database management and lifecycle control, with CloudNativePG exemplifying this approach. Bartolini asserts that owning hardware allows organizations to better manage costs, especially for resource-intensive AI workloads, and that moving to bare metal can significantly enhance performance. A cultural shift is necessary for success, with DBAs needing to adapt to cloud-native environments. Bartolini encourages DBAs to develop a broader understanding of Kubernetes to enhance collaboration across teams. He warns that the database team cannot drive change alone and must align with the entire infrastructure direction to avoid dependency on proprietary tools that limit independence and innovation.

Tech Optimizer

April 8, 2026

PostgreSQL logical replication: How to replicate only the data that you need

Many organizations using PostgreSQL face challenges in replicating data across different logical databases while controlling shared information. PostgreSQL 15 introduces native logical replication with column-level and row-level filtering within publications, allowing precise control over data transfer between PostgreSQL databases. Logical replication operates on a publish-subscribe model, where the source database logs changes to the Write-Ahead Log (WAL) and applies publication filters to transmit only the relevant data to the target database. Two filtering modes are available: column-level filtering allows users to specify which columns to replicate, while row-level filtering uses WHERE clauses to determine which rows to include. Both filtering modes can be combined in a single publication. The SQL syntax for creating publications and subscriptions is consistent across various PostgreSQL environments, with specific configurations required for enabling logical replication. Use cases for logical replication include multi-tenant SaaS data isolation, regional data distribution for ecommerce, PCI DSS compliance in financial services, development and testing environments, and retail inventory management. Prerequisites for implementing logical replication include using PostgreSQL 15 or later, ensuring network connectivity, having a user with replication privileges, enabling logical replication on the source instance, and monitoring WAL retention. Logical replication has limitations, such as the need for a replica identity for UPDATE and DELETE operations, the non-replication of DDL changes and sequences, and potential performance overhead during initial synchronization and ongoing replication. After testing, it is advisable to clean up by removing replication resources to prevent unnecessary costs.

Tech Optimizer

April 6, 2026

36 Malicious npm Packages Exploited Redis, PostgreSQL to Deploy Persistent Implants

Cybersecurity researchers have discovered 36 malicious packages in the npm registry that impersonate Strapi CMS plugins. These packages exploit Redis and PostgreSQL, deploy reverse shells, harvest credentials, and establish persistent implants. Each package consists of three files—package.json, index.js, and postinstall.js—without descriptions or repositories, and all use version 3.6.8 to mimic legitimate Strapi plugins. The malicious packages follow a naming convention starting with "strapi-plugin-" and were uploaded by four accounts within 13 hours. The identified packages include names like strapi-plugin-cron, strapi-plugin-database, and strapi-plugin-server. The malicious code is embedded in the postinstall script, executing automatically upon installation with the same privileges as the user. The payloads evolve from exploiting Redis for remote code execution to attempting direct PostgreSQL database exploitation and deploying persistent implants for remote access. The campaign appears to target cryptocurrency platforms, as indicated by the focus on credential theft and digital assets. Users of these packages are advised to assume compromise and rotate credentials. This incident reflects a broader trend of supply chain attacks in the open-source ecosystem, with recent examples including credential exfiltration payloads in GitHub repositories and compromised GitHub Actions workflows. Group-IB reported that software supply chain attacks are increasingly reshaping the cyber threat landscape, targeting trusted vendors and open-source software to gain access to downstream organizations.

Tech Optimizer

April 5, 2026

Linux 7.0 Cuts PostgreSQL Performance in Half

An AWS engineer reported a significant drop in PostgreSQL throughput on Linux 7.0, with performance reduced to approximately half of its previous capability. Benchmark tests showed that the removal of the PREEMPT_NONE scheduling option was the main cause of this regression. On a 96-vCPU Graviton4 instance, throughput measured at just 0.51x compared to earlier kernel versions. Salvatore Dipietro from Amazon/AWS conducted benchmarking analysis of PostgreSQL 17, revealing that Linux 7.0 delivered only 0.51x the throughput of its predecessors. The root cause was traced to kernel commit 7dadeaa6e851, which eliminated PREEMPT_NONE as the default option, leading to increased contention due to the new PREEMPT_LAZY model. Profiling data indicated that 55% of CPU time is consumed by spinning in PostgreSQL’s spinlock, causing significant performance degradation. When a revert patch was applied, throughput rebounded to 1.94x the baseline. The decision to restrict preemption modes in Linux 7.0 aimed to address issues within the kernel's scheduling model. Dipietro proposed a patch to restore PREEMPT_NONE, but kernel developers suggested PostgreSQL adopt the rseq time slice extension instead. Database operators running PostgreSQL on Linux face potential performance reductions with the upgrade to Linux 7.0.

Tech Optimizer

April 4, 2026

AWS Engineer Reports PostgreSQL Performance Halved By Linux 7.0, But A Fix May Not Be Easy

An engineer from Amazon/AWS reported a significant performance regression in PostgreSQL when running on the nearly finalized Linux 7.0 kernel, with throughput dropping to about half of previous kernel versions. The regression, observed on a Graviton4 server, is attributed to increased time spent in a user-space spinlock due to changes in preemption modes in Linux 7.0. A patch to revert to PREEMPT_NONE as the default preemption model has been submitted but may not be adopted. Peter Zijlstra suggested that PostgreSQL should adapt to utilize the Restartable Sequences (RSEQ) time slice extension to mitigate the performance drop. If this adaptation is accepted, the responsibility for the performance decline may shift to PostgreSQL, potentially affecting users until the database is updated. The stable release of Linux 7.0 is expected in about two weeks, coinciding with the launch of Ubuntu 26.04 LTS.

Tech Optimizer

April 1, 2026

EDB Postgres® AI Delivers Superior Predictability vs. Cloud Data Warehouses in High-Concurrency Benchmark, Unveils Q1 Platform Updates to Power the Agentic AI Era

Independent benchmarking by McKnight Consulting Group shows that EDB Postgres AI for WarehousePG provides significant cost efficiency and performance consistency, with organizations potentially saving up to 58% in total cost of ownership compared to leading cloud data warehouse solutions. The evaluation compared EDB PG AI against competitors like Snowflake, Databricks, Amazon Redshift, and Hive on Apache Iceberg using a 10TB extended TPC-DS dataset, focusing on high-concurrency mixed workloads. Key findings include: - EDB PG AI demonstrated unmatched cost efficiency, with an annual cost of ,886 compared to Snowflake’s ,953 for a multi-cluster setup. - It exhibited superior concurrency handling, with the lowest performance slowdown of 2.7x when scaling from one to five concurrent users, outperforming Snowflake (3.9x), Redshift (4.0x), and Databricks (4.1x). - EDB PG AI's core-based, capacity-pricing model eliminates unpredictable pricing fluctuations associated with consumption-based models. EDB announced Q1 2026 platform updates, including: - GPU-Accelerated Analytics for 50–100x faster analytics on large datasets. - Enhanced Agent Studio for quicker AI agent development and deployment. - Upgraded Vector Engine for improved indexing speed and efficiency. - WarehousePG Enterprise Manager for simplified management of MPP workloads. - Agentic Database Management with a native chatbot for natural language database management. - Certification as a mission-critical data layer for the Red Hat Ansible Automation Platform.