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Short Summary: PostgreSQL can slow down when range queries and frequent data updates rely on the same indexes. This guide shows how to spot the problem and use Devart tools to reduce B-Tree index conflicts, improve query plans, and manage bi-weekly data updates in AWS Aurora.

We are thrilled to announce a set of product updates across our dotConnect data providers and Entity Developer. The new release adds support for Entity Framework Core 10, introduces AI-focused vector data types across major databases, and extends compatibility with the newest platform capabilities such as SQL Server 2025, Oracle 26ai, and Microsoft Entra authentication.

We are happy to announce the release of Review Assistant 4.3, introducing support for integration with Visual Studio 2026 and a more practical permissions model for viewing project reports.

We’re excited to share Code Compare 5.5 R1, the latest update to our code comparison and merge tool. This release adds integration support for Visual Studio 2026, so teams can compare changes and resolve merge conflicts directly within the IDE workflow they already use. With Code Compare 5.5 R1, developers can review differences, apply merges, and handle conflicts in Visual Studio 2026 using the same comparison experience they rely on across projects and repositories.

Short Summary: Sometimes URL paths repeat by mistake because of tracking problems or redirect loops.. In this guide, you’ll learn how to find and count those repeats using Trino SQL. By using simple SQL tools like CTEs, arrays, and window functions, you can break a long link into smaller pieces and clean up the data without using complex regex.

Short Summary: In this guide, we address performance problems that occur when PostgreSQL queries very large tables containing low-cardinality boolean fields. It also demonstrates how composite indexes, created and tested with Devart tools, allow PostgreSQL to locate the required rows directly instead of scanning the entire table.

Short Summary: This article explains how to expand your CLI query tool so it can handle multiple databases. First, we focus on key relational systems, then move to data warehouses. We’ll use dbForge Edge as a reference point, showing how different databases can be managed in one place while keeping automation simple.

Picking an SQLite ODBC driver is like choosing a key; you need one that opens every door cleanly, without snapping or jamming. The right driver must connect your data effortlessly—no errors, no limitations. It also has to withstand real challenges: complex queries, cross-platform environments, and large datasets. In this guide, we’ll show you which 2026 drivers stand up to these demands, so you can pick the one that won’t let you down.

Short Summary: Counting related records across multiple dependent tables can produce wrong totals or slow queries when standard joins are used. This article explains a more reliable way to do this by counting each table separately, applying date filters, and checking that the query still runs well on large datasets. Tools such as dbForge Edge can also help if needed.

Short Summary: Different databases use different SQL syntax for simple tasks like subtracting days from a date. In this post, we show how these differences appear across databases such as MySQL, PostgreSQL, SQL Server, Oracle, and H2. We also explain how dbForge Edge helps teams work with them in one place while keeping application logic consistent.