Monthly Archive

Analyze Data & Create Reports Across Databases with dbForge Edge

Oct 13, 2026 By Devart In Devart

Analyze, visualize, and report database data across multiple database systems and cloud services with dbForge Edge. Write SQL queries or generate them with AI Assistant , analyze data with Pivot Tables, explore related records with Master-Detail Browser, visualize findings in charts, and create clear database reports — all within one multi-database solution.

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Data Analysis & Reporting Across Databases and Cloud Services With dbForge Edge

Oct 12, 2026 By Devart In Devart

Analyze data and create reports across multiple database systems and cloud services with dbForge Edge. dbForge Edge brings SQL querying, data analysis, visualization, reporting, and automation into one multi-database solution. Use the built-in SQL development tools and AI Assistant to retrieve data, analyze large datasets with pivot tables, inspect related records with Master-Detail Browser, visualize findings in charts, and create clear and compelling data reports.

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SecureBridge 12.1, EntityDAC 4.1, and dbExpress drivers: Support for RAD Studio 13 Florence Release 2, SQL Server 2025, and MySQL 9.7

Oct 9, 2026 By DAC Team In Devart

New versions of SecureBridge, EntityDAC, and dbExpress drivers are out. All three now work with RAD Studio 13 Florence Release 2 and offer improved support for the Arm64EC target platform. Devart dbExpress drivers also add support for Microsoft SQL Server 2025 and MySQL 9.7, while SecureBridge gains SFTP upload resume, multipart/form-data support, and a new SSL/TLS demo.

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Read more about SecureBridge 12.1, EntityDAC 4.1, and dbExpress drivers: Support for RAD Studio 13 Florence Release 2, SQL Server 2025, and MySQL 9.7

pgvector for RAG: When you don't need a dedicated vector database

Oct 6, 2026 By Rosemary Asufi In Devart

Dedicated vector databases have become such a standard part of the RAG conversation that teams often add one before they have proved they need it. According to studies, over 70% of companies using LLMs are using vector databases and RAG to customize their models. That shows how quickly the pattern has become normal. However, it does not mean every RAG application needs a separate retrieval system. If your application already runs on PostgreSQL, pgvector may be enough.