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PostgreSQL cost model: estimating the cost of flushing temp buffers to disk
Tech Optimizer
March 29, 2026

PostgreSQL cost model: estimating the cost of flushing temp buffers to disk

The project focuses on enabling temporary tables in PostgreSQL's parallel query execution by benchmarking sequential writes and reads of temporary buffers. Functions were introduced to measure buffer flush operations, and tests were conducted to estimate the cost of flushing temporary table buffer pages to disk. Findings indicate that sequential writes are about 30% slower than reads, leading to a proposed cost model. Temporary tables have limited parallel usage due to their function as relational variables and the complexity of parallel workers accessing the leader process's local state. Two enterprise PostgreSQL distributions already support parallel operations on temporary tables, and discussions on logical replication of DDL highlight the need for improved tooling for temporary tables. A significant challenge is that temporary buffer pages are local to the leader process, and if not flushed to disk, parallel workers cannot access them. A comment from 2015 suggests flushing the leader's temporary buffers to disk before parallel operations to allow workers to scan the table in parallel. However, this raises concerns about the cost of writing buffers versus the benefits of parallelism. The benchmarking toolkit includes modifications to PostgreSQL to facilitate measurement of local buffers. Two key commits added statistics infrastructure to track allocated and dirty local buffers and UI functions to manage buffer operations. The methodology involves creating a temporary table, flushing buffers, measuring I/O, and evaluating scan overhead. The tests reveal that the cost of writing a temporary table approximates the cost of a sequential page, leading to a proposed formula for flushing costs. The results show that larger buffer sizes lead to higher write overhead and increased variability. A comprehensive formula for pre-flushing temp buffers is suggested, factoring in the number of dirtied and allocated local buffers. Next steps include adding planner flags for temporary objects, implementing executor support for worker access to temporary table storage, introducing a temp-buffer flush operation, and integrating the cost model into the planner for parallel scans of temporary tables.
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Tech Optimizer
March 26, 2026

EDB Highlights CloudNativePG 1.29, Previews Kubernetes-Native Data Protection at KubeCon Europe

EnterpriseDB (EDB) has released CloudNativePG 1.29, an open-source PostgreSQL operator for Kubernetes, featuring modular extensions and enhanced supply chain security. This version allows users to install only necessary PostgreSQL extensions, including options for AI-driven vector search, while ensuring the use of verified components. EDB is also previewing a new enterprise data protection solution for its EDB Postgres AI for CloudNativePG operator, which includes zero data loss through write-ahead log streaming, centralized management, disaster recovery support, and end-to-end encryption. EDB emphasizes its commitment to data and AI sovereignty and security compliance in Europe, adhering to regulations like the EU Cyber Resilience Act, and aims to support PostgreSQL operations across on-premises and cloud environments to avoid vendor lock-in.
EDB Highlights Community Release of CloudNativePG 1.29 and Previews Exclusive Kubernetes Data Protection at KubeCon Europe
Tech Optimizer
March 26, 2026

EDB Highlights Community Release of CloudNativePG 1.29 and Previews Exclusive Kubernetes Data Protection at KubeCon Europe

EnterpriseDB (EDB) has released CloudNativePG 1.29, an open-source Postgres operator for Kubernetes, and introduced an enterprise-grade data protection solution for its commercial CNPG operator. Open-source strategies are crucial for 80% of major enterprises in the EMEA region, with only 13% achieving success in AI and data initiatives through sovereign data platforms. The EU Cyber Resilience Act mandates secure software supply chain practices. CloudNativePG has gained over 8,000 stars on GitHub and now features modular extensions and built-in supply chain security. EDB is developing a Kubernetes-native data protection solution offering Zero Data Loss and centralized management. This solution supports compliance with the EU Cyber Resilience Act and ensures operational control while reducing cloud infrastructure costs. EDB Postgres® AI is positioned as a secure, compliant, and scalable sovereign data and AI platform.
Building a High-Performance Postgres Time Series Stack with Iceberg
Tech Optimizer
March 19, 2026

Building a High-Performance Postgres Time Series Stack with Iceberg

Postgres extensions, specifically pg_lake, pg_partman, and pg_incremental, provide a vendor-agnostic, open-source solution for managing high-performance time series data. PostgreSQL serves as the foundation, while pg_partman automates time partition management, pg_lake connects Postgres with data lakes for offloading cold data, and pg_incremental processes append-only data in batches. These extensions are maintained by the Postgres team at Snowflake. An example system for monitoring temperature readings uses local storage for recent data and transitions cold data to an Apache Iceberg table on S3. The process includes creating a partitioned table in Postgres, establishing an Iceberg table, using pg_incremental for data appending, eliminating old partitions with pg_partman, and querying from both local and cold tables to optimize storage and costs. A time-partitioned table enhances performance by allowing efficient deletion of outdated data, speeding up queries, and reducing fragmentation.
EDB Accelerates Postgres for the Agentic Workforce Era with NVIDIA AI Infrastructure and Interactive Analytics
Tech Optimizer
March 17, 2026

EDB Accelerates Postgres for the Agentic Workforce Era with NVIDIA AI Infrastructure and Interactive Analytics

EnterpriseDB (EDB) has advanced its integration with NVIDIA's cuDF for Apache Spark to enhance Postgres® performance on NVIDIA AI infrastructure, achieving analytics capabilities up to 100 times faster than traditional methods. EDB emphasizes the need for a real-time analytics framework to address challenges posed by fragmented data silos and inefficient analytics processes. Key features of EDB Postgres AI include GPU-acceleration for interactive analytics, NVIDIA NIM model serving, fully air-gapped support for private registries, and high-speed retrieval with NVIDIA NeMo Retriever. Research indicates only 13% of enterprises have transitioned to production-scale agentic deployments, which report five times higher ROI. The EDB PG AI Analytics Engine can achieve 50–100x faster analytics on large datasets, supports lakehouse architectures, and ensures workload isolation and governance. EDB PG AI is positioned as a secure, compliant, and scalable platform for operationalizing data and AI workloads.
EDB tops new ranking of commercial Postgres backers
Tech Optimizer
March 13, 2026

EDB tops new ranking of commercial Postgres backers

EnterpriseDB (EDB) has launched the Postgres Vitality Index, which ranks commercial contributors to PostgreSQL, highlighting EDB's claim of over 30% of contributions. The index evaluates contributions based on core code, ecosystem extensions, and community support. EDB is positioned ahead of AWS and Microsoft in contributions. EDB's product strategy includes EDB Postgres AI, addressing data sovereignty and governance for AI systems, emphasizing a hybrid architecture for various workloads. EDB aims to enhance Postgres's readiness for enterprise AI, while also publishing resources related to Postgres and AI architecture. The index's introduction aligns with an increase in managed Postgres offerings and tools from various vendors.
Why Postgres® has won as the de facto database: Today and for the agentic future
Tech Optimizer
March 12, 2026

Why Postgres® has won as the de facto database: Today and for the agentic future

The AI economy is projected to reach a trillion by 2028, leading 95% of major global enterprises to establish AI and data platforms within two years, although only 13% have succeeded so far. Successful integration of agentic AI requires moving away from outdated architectures to a cohesive data and AI approach. Currently, 81% of successful enterprises utilize open-source strategies, with over 40% standardizing on PostgreSQL. PostgreSQL's extensibility allows for the integration of diverse data types, essential for AI applications. It provides a unified database engine that mitigates issues associated with fragmented architectures. PostgreSQL benefits from a large independent developer community, which enhances its innovation and adaptability. To thrive in the future, organizations must abandon legacy systems and leverage PostgreSQL's capabilities for a sovereign data platform.
The Postgres® Vitality Index: Enterprises Rush to Postgres, and EDB Continues to Lead the Foundation for Sovereign Enterprise AI
Tech Optimizer
March 12, 2026

The Postgres® Vitality Index: Enterprises Rush to Postgres, and EDB Continues to Lead the Foundation for Sovereign Enterprise AI

EnterpriseDB (EDB) has launched the Postgres Vitality Index to evaluate the commercial contributions shaping PostgreSQL's future. The index indicates that Postgres is the most strategically invested-in database globally, with EDB as the leading contributor, accounting for over 30% of contributions. Postgres is favored by over 55% of developers, reflecting its growing adoption among major tech firms. The index assesses contributions in three areas: core advancements in the PostgreSQL codebase, ecosystem enhancements through extensions and tools, and community support. EDB's Postgres AI platform addresses the need for data and AI sovereignty, offering a hybrid architecture for governance and flexibility. EDB has also published a guide on building AI platforms with Postgres, which will be distributed at NVIDIA's GTC event.
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