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EDB Postgres® AI Outperforms Vector Databases, Lakehouses, and Document Stores for Agentic AI on Speed, Accuracy, and Cost
Tech Optimizer
July 29, 2026

EDB Postgres® AI Outperforms Vector Databases, Lakehouses, and Document Stores for Agentic AI on Speed, Accuracy, and Cost

EDB Postgres AI is a pioneering solution that integrates intelligence and data on a unified sovereign foundation, eliminating the need for ETL processes, data duplication, and separate vector stores. Independent benchmarks show that EDB Postgres AI outperforms competing platforms in speed, accuracy, and cost-effectiveness. A study by McKnight Consulting Group indicates that EDB Postgres AI excels in key performance metrics, including query latency, accuracy, cost, and data freshness, outperforming specialized vector databases and other managed Postgres platforms. EDB Postgres AI achieves median query latencies of 50 milliseconds at a scale of 50 million vectors, making it 80x faster than Databricks, 21x faster than MongoDB Atlas, and up to 2x faster than alternatives like Aurora and Crunchy Bridge. It also delivers the highest recall rates for core vector searches, surpassing competitors like MongoDB and Databricks. In tests involving concurrent retrievals, EDB Postgres AI completed a three-arm agent loop in 27 milliseconds, significantly faster than other platforms. In terms of cost efficiency, EDB Postgres AI offers 76x better price performance than Databricks, 34x better than MongoDB, and 23%–28% better than the nearest managed Postgres competitors when considering query speed. The architecture of EDB Postgres AI allows for the integration of vector, filtered, and full-text retrieval in a single query path, ensuring real-time data access and eliminating the need for separate systems.
EDB launches agentic Postgres AI with governance tools
Tech Optimizer
June 26, 2026

EDB launches agentic Postgres AI with governance tools

EDB has introduced new features for its Postgres AI platform, including an agentic database and converged analytics capabilities, allowing enterprises to run AI agents alongside transactional workloads on a unified PostgreSQL foundation. The platform includes governance tools that position control mechanisms at the data layer and integrates AI processing with operational data, enabling businesses to connect live records with AI systems without transferring sensitive information. The agentic database can monitor over 200 metrics, identify issues, suggest changes, and apply fixes automatically based on user-defined policies. It consolidates various data types through a single SQL interface, significantly accelerating database tuning processes and enhancing application performance. EDB has also expanded its analytics capabilities with a zero-ETL architecture for real-time analysis and large-scale warehousing. EDB PG AI for ClickHouse targets real-time analysis, while EDB PG AI for WarehousePG focuses on historical analysis at petabyte scale. The platform claims up to 30 times faster query performance compared to legacy systems and improved scaling efficiency. EDB's platform integrates vector search and retrieval for AI agents, demonstrating lower query latency and higher retrieval accuracy than competitors. NTT East is using EDB PG AI for AI-driven network operations, while the governance feature manages agent access at the data querying point using native Postgres roles and row-level security. The platform can be deployed on-premises, in hybrid environments, or across cloud infrastructures, with partnerships including Dell, IBM, Nvidia, Red Hat, and Supermicro.
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Tech Optimizer
June 20, 2026

EDB Reports Growing Adoption of Postgres AI as Enterprises Build Sovereign AI Foundations

EnterpriseDB (EDB) reported increased global adoption of its EDB Postgres AI (EDB PG AI) platform for managing mission-critical workloads. Research by MIT Technology Review Insights found that organizations prioritizing AI and data sovereignty achieve five times the return on investment. The Industrial Bank of Korea (IBK) migrated 15 core systems to EDB PG AI, reducing licensing costs and enhancing operational flexibility. Shinhan EZ Insurance transitioned its core system to the public cloud using EDB PG AI, achieving 24/7 service and scalability for AI workloads. Other companies like MNTN, Euronext FX, and Kyobo Book Centre are also leveraging EDB PG AI for various applications. EDB has received industry recognition, including being named among the most innovative companies in data and awarded for its data management solutions. EDB PG AI integrates transactional, analytical, and AI workloads, providing a secure and scalable platform for enterprises.
Windows Platform Security and the Race to Secure AI Agents
Winsage
June 19, 2026

Windows Platform Security and the Race to Secure AI Agents

Microsoft has introduced the Microsoft Execution Containers (MXC) SDK to establish Windows as a reliable operating system for autonomous agents, focusing on containment, identity, and manageability. The MXC framework serves as a policy-driven execution layer for agents on Windows and Windows Subsystem for Linux (WSL), allowing developers to set access permissions using JSON or TypeScript. It employs process and session isolation for agent containment and identity. Future enhancements will include micro-VM support for high-risk tasks and integration with Windows 365 for cloud PC workloads. IT teams can manage MXC policies through Entra ID and Intune, while Defender and Purview provide protection and observability. The MXC framework is built on Microsoft's security initiatives, including Secure Boot and passwordless sign-in, allowing agents to inherit a secure foundation. However, early commentary expresses caution regarding MXC's perception as a comprehensive security solution, noting issues with overly permissive policies and the lack of outbound network filtering. Other platforms, such as Linux, are also enhancing security for agents with kernel-level isolation and secure environments like NVIDIA's OpenShell runtime. Various projects are focusing on agent sandboxes within Kubernetes, employing technologies like gVisor and Kata Containers for isolation. Overall, no singular dominant platform security model for AI agents has emerged, with Windows' MXC still considered nascent compared to existing solutions in Linux and Kubernetes ecosystems.
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Tech Optimizer
June 18, 2026

Companies turn to EnterpriseDB for AI data control

Organizations are increasingly adopting EnterpriseDB's EDB Postgres AI platform due to a rising demand for enhanced control over data in AI systems, particularly in sectors like banking, insurance, retail, and trading. Research from MIT Technology Review Insights indicates that prioritizing AI and data sovereignty significantly predicts success in AI initiatives, with such organizations achieving five times the return on investment. In South Korea, the Industrial Bank of Korea migrated 15 core systems to EDB Postgres AI, citing significant reductions in licensing costs compared to Oracle and improved scalability for future AI services. Shinhan EZ Insurance transitioned its core system to the public cloud using EDB, overcoming challenges related to legacy database licensing and emphasizing the importance of operational stability. Beyond finance, companies like MNTN, Euronext FX, and Kyobo Book Centre have adopted the platform to reduce vendor reliance, manage data workloads, and enhance compliance control. MNTN uses EDB for large-scale analytical processing, Euronext FX has implemented it across four data centers, and Kyobo Book Centre migrated from a costly data warehouse to the EDB solution. A common trend among these deployments is the use of a single Postgres-based platform for transactional processing, analytics, and AI tasks, reflecting an industry initiative to simplify operations and reduce costs. Hensley noted the critical convergence of AI systems with operational data, as AI agents operate against live data in high-volume workflows, highlighting the drawbacks of using separate platforms for transactions and analytics. EnterpriseDB has also received industry accolades for its data management and contributions to the open-source community, reinforcing its market position.
Neon vs Supabase 2026: $1B Deal, Scale-to-Zero
Tech Optimizer
June 14, 2026

Neon vs Supabase 2026: $1B Deal, Scale-to-Zero

Neon and Supabase are two managed PostgreSQL platforms with distinct approaches. Neon adopts a serverless architecture that separates storage and compute, allowing databases to scale to zero when idle and enabling rapid database branching. Supabase, in contrast, provides a comprehensive backend-as-a-service that includes authentication, file storage, real-time subscriptions, and edge functions, all built around PostgreSQL. In 2025, Databricks acquired Neon for approximately billion, motivated by the observation that around 80% of databases created on Neon were generated by AI agents. Post-acquisition, users experienced reduced storage costs and improved pricing structures, although concerns arose regarding Neon's independence. Neon features instant database branching and a scale-to-zero capability, while Supabase offers a fully integrated backend with built-in authentication and storage. Neon operates on a usage-based pricing model, whereas Supabase has a flat-tier pricing structure. Both platforms support the pgvector extension for AI applications, but Supabase is fully open-source and allows for self-hosting, unlike Neon. The developer community recognizes Supabase for its ease of use and rapid application development capabilities, while Neon is praised for its innovative serverless features and cost efficiency. Migration between the two platforms is simplified due to their shared PostgreSQL foundation.
As the Agentic Era Reshapes the Data Layer, Enterprises Build Their Sovereign Foundation on EDB Postgres® AI
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.
A guide to agentic AI: How Windows is now going to do more things for you
Winsage
June 5, 2026

A guide to agentic AI: How Windows is now going to do more things for you

Microsoft is advancing in the field of artificial intelligence with the introduction of agentic AI, which aims to perform tasks on behalf of users rather than just responding to queries. A key feature is 'autoagents,' starting with Scout, which will integrate into Microsoft 365 applications and autonomously manage tasks like monitoring communications and summarizing documents. Scout is currently being rolled out to select users and is designed with safety measures, including Execution Containers to control resource access and mitigate risks. Additionally, Microsoft has launched Discovery, a tool for enhancing scientific research, and Rayfin, which simplifies application development for individual creators.
Build 2026: Furthering Windows as the trusted platform for development
Winsage
June 3, 2026

Build 2026: Furthering Windows as the trusted platform for development

Build is an annual event focused on connecting with the global developer community and sharing innovations. Feedback from developers emphasizes the need for a frictionless and adaptable platform for seamless development across various environments. Key announcements include: - Coreutils for Windows: A suite of Linux-like command line utilities available natively on Windows. - WSL containers: A forthcoming public preview feature for creating and interacting with Linux containers. - Windows Development Skills: Structured knowledge for building native Windows apps using WinUI3 and WinApp CLI, now generally available. - Intelligent Terminal: An experimental feature integrating context-aware intelligence into the terminal for improved debugging and task execution. - Windows Developer Configurations: A WinGet-powered setup for distraction-free development, now generally available. - Windows 365 with Developer Configuration: A pre-configured cloud-based development environment in public preview. For security, the announcements include: - Microsoft Execution Containers (MXC) SDK: A policy-driven execution layer for agent access and containment, available in early preview. - Agent 365 integration: Enhances security for agents with protections from Defender, Entra, Intune, and Purview, available in preview. - OpenClaw: Runs securely on Windows using MXC for easy installation of agent connections. - NVIDIA's OpenShell: A deployment package for autonomous agents on Windows, built on MXC. - Windows 365 for Agents: Secure Cloud PCs for executing enterprise workflows, now generally available. For AI capabilities: - Aion 1.0 Instruct: An on-device small language model for local workloads, available soon. - Expanded Windows AI APIs: Now accessible on more Windows 11 PCs, enhancing local AI capabilities. - Surface RTX Spark Dev Box: A device for developers featuring NVIDIA RTX Spark silicon for local AI workloads. - DGX Station for Windows: A powerful AI supercomputer for developing agents, coming in Q4. - Project Solara: A platform for agent-driven experiences, simplifying development across environments. - New Speech Recognition API: Real-time, on-device transcription capabilities. - Expansion of Windows AI APIs across GPUs and CPUs: Now available for broader hardware support. Windows is enhancing its security framework to reduce risks and ensure robust protection for applications.
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