This guide shows how to aggregate across multiple related tables without inflating counts or degrading performance. Learn why standard joins produce misleading totals, how separate aggregations fix the math, and how to keep the query efficient even as data volume and table relationships grow.
This guide explains how to reconstruct the state of related data at a precise moment using temporal LEFT OUTER JOINs in SQL Server. Learn how synchronized time clauses prevent mismatched records, why historical joins produce unexpected NULLs, and how to keep queries accurate and efficient against large history tables.
How about ending this year on a major note? Meet dbForge 2025.3, our new release that covers the entire dbForge product line and brings lots of useful stuff to the table. Without further ado, let's take a look!
This article provides a clear overview of Microsoft Fabric Data Warehouse, its structure, capabilities, and when to use it. It contrasts the Warehouse with the Lakehouse, outlines benefits for analytics teams, and demonstrates how dbForge for SQL Server improves productivity when working with Fabric’s SQL-based environment.
Automate your database like a pro. SQL Server Agent jobs handle backups, ETL, and monitoring, so you don’t have to. Learn how to build, schedule, and manage jobs efficiently using SSMS, T-SQL, or GUI tools. Read on!
This guide focuses on the SQL NTILE function and how it distributes data into quartiles, deciles, or percentiles. With clear syntax breakdowns, practical SQL Server examples, and real-world scenarios, it demonstrates how NTILE supports ranking, grouping, and reporting while complementing other SQL window functions for deeper analytical insights.
New dbForge milestone is achieved! This time, it brings us enhancements in AI Assistant, long-awaited user interface improvements, and further significant advancements in cloud support underway.
Interested in learning more? Let's get started!
This guide to SQL formatting best practices shows how to write queries that are consistent, readable, and scalable. By applying rules for capitalization, indentation, clause order, and naming, teams create SQL that’s easier to review, debug, and maintain across projects, reducing technical debt over time.