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Snowflake Postgres Unifies Your Apps, Analytics and AI
Tech Optimizer
June 18, 2026

Snowflake Postgres Unifies Your Apps, Analytics and AI

Every enterprise operates in two realms: one for real-time applications that process orders and engage customers, and another for analytics platforms that extract insights and drive AI. Snowflake is introducing Snowflake Postgres to bridge these realms with two key features: 1. Data mirroring, which is an always-on replication feature between Postgres and Snowflake, set to enter public preview soon. 2. Postgres for data lakes, allowing synchronization with analytics using open formats like Iceberg, which will be generally available shortly. These features aim to simplify the connection between transactional and analytical data, reducing the need for complex ETL pipelines. Customer feedback indicates that transferring data between OLTP and OLAP databases is the most challenging infrastructure task, leading to costs and issues such as data inconsistencies and delayed decision-making. Snowflake Postgres offers a simplified integration method with low-latency data mirroring that automatically maintains target tables in Snowflake to reflect the current state of source tables in Postgres. This setup can be configured easily through various interfaces or a single SQL command.
SQL Server may be too lucrative for Microsoft to ditch, but too legacy to love
Tech Optimizer
June 18, 2026

SQL Server may be too lucrative for Microsoft to ditch, but too legacy to love

Microsoft's Build event highlighted its new AI agent, Scout, while SQL Server received limited attention, raising concerns about its future following Rohan Kumar's departure. Arun Ulag now oversees SQL Server, but analysts note a shift in priorities with SQL Server seemingly less emphasized. The 2022 SQL Server release was viewed as more of a marketing effort than a response to customer needs. Despite the introduction of vector search in SQL Server 2025, competitors had already offered similar features. Microsoft is shifting towards open-source solutions and PostgreSQL, although it reassured users of its commitment to SQL Server. SQL Server, launched in 1989, remains popular, ranking behind Oracle and MySQL. The on-premises database market is lucrative, generating significant revenue, and SQL Server holds a substantial share. Microsoft is unlikely to abandon this profitable segment, aiming to transition users to Azure SQL and SQL database within Fabric. However, migration compatibility issues may arise. Microsoft is also investing in PostgreSQL offerings to compete in the cloud database market, which is evolving rapidly. AWS currently leads in cloud DBMS revenue, posing a challenge for Microsoft. Despite uncertainties, support for SQL Server 2025 is guaranteed until 2036.
Announcing Lakebase Search: agent-native retrieval built into Lakebase Postgres
Tech Optimizer
June 18, 2026

Announcing Lakebase Search: agent-native retrieval built into Lakebase Postgres

Lakebase Search is a hybrid vector and full-text retrieval system integrated into Lakebase, now in beta on AWS and Azure. It utilizes two Postgres extensions: lakebase_vector and lakebase_text, allowing agents to operate on a single data backend. Agents manage four times more databases than human users and require real-time access to indexed data. The system features a tiered architecture that stores cold data in cost-effective object storage while keeping active data in local NVMe, significantly reducing costs. The lakebase_vector extension offers 32x compression for vectors, allowing a billion vectors to fit into under 10GB of RAM. The lakebase_text extension provides BM25 relevance ranking without high RAM usage. Benchmarking shows that Lakebase Search can efficiently handle large-scale workloads, achieving high recall and low latency with reduced resource requirements compared to traditional architectures. The system allows for continuous search experimentation and dedicated retrieval engines for each agent, enhancing operational efficiency and scalability.
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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.
Why Oracle’s OCI Database with PostgreSQL matters for serious workloads
Tech Optimizer
June 18, 2026

Why Oracle’s OCI Database with PostgreSQL matters for serious workloads

Oracle has launched the OCI Database with PostgreSQL, a managed PostgreSQL service designed for seamless deployment within the Oracle Cloud. This service includes lifecycle management, automated backups, and monitoring, allowing users to customize their database configurations easily. A key feature is the cross-region warm standby, which enhances disaster recovery by enabling users to create replica databases in secondary regions that replicate data from the primary database. The service enforces a strict 5-minute recovery point objective (RPO) and simplifies the setup process for operations teams. The OCI Database with PostgreSQL is positioned against offerings from AWS and Azure, targeting organizations that prefer a managed PostgreSQL experience. However, compliance challenges, such as the lack of FedRAMP certification, may hinder adoption for certain sectors. The product is available on OCI with usage-based pricing and is aimed at cloud teams needing managed operations and disaster recovery for PostgreSQL databases.
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Tech Optimizer
June 17, 2026

Databricks Puts AI Search Inside Postgres

Databricks has introduced Lakebase Search, a feature that integrates advanced search capabilities into its Lakebase Postgres database, currently in beta on AWS and Azure. This feature aims to enhance AI agent development by embedding native retrieval functions within the data backend. It addresses the challenge of "Vector Bloat Cost" by utilizing tiered storage for optimized data access and retrieval efficiency. Lakebase Search includes two new Postgres extensions, lakebase_vector and lakebase_text, which enable hybrid search capabilities that combine vector and full-text search functionalities. This integration streamlines the AI agent loop, improving agent-first ergonomics and allowing developers to create more efficient AI systems.
Snowflake Simplifies Postgres Data Sync
Tech Optimizer
June 17, 2026

Snowflake Simplifies Postgres Data Sync

Snowflake has introduced features to improve data integration between PostgreSQL and its platform, addressing challenges in transferring data between online transaction processing (OLTP) and online analytical processing (OLAP). One key feature is data mirroring, which offers low-latency replication for PostgreSQL, automatically maintaining target tables to reflect source changes with minimal setup effort. These advancements aim to simplify data integration, reduce costs associated with ETL tools, and facilitate real-time insights, enhancing operational efficiency for organizations.
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.
Why Use App-Level Auth When Every Database Has Auth? (Splunk Enterprise CVE-2026-20253 Pre-Auth RCE)
Tech Optimizer
June 13, 2026

Why Use App-Level Auth When Every Database Has Auth? (Splunk Enterprise CVE-2026-20253 Pre-Auth RCE)

On June 10th, Splunk released an advisory for CVE-2026-20253, a high-severity vulnerability with a CVSS score of 9.8 that requires no authentication. The vulnerability is associated with the PostgreSQL Sidecar Service Endpoint and affects Splunk Enterprise versions 10 and above. In default installations, the service is not installed on Windows but is installed and enabled by default on AWS. The vulnerability allows unauthorized users to create and truncate arbitrary files through an API that lacks authentication controls. Additionally, it enables the execution of SQL commands via a backup and restore mechanism, potentially leading to remote code execution (RCE). A Detection Artefact Generator has been developed to help organizations assess their vulnerability to this issue.
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