Microsoft Azure offers Azure Elastic Job agent as a managed service, enabling efficient scheduling of T-SQL workloads on Azure SQL Databases. Learn how to configure the service in this article.
2024-06-07 (first published: 2024-05-24)
1,805 reads
In part 2 of this series, I showed an example implementation of distributing a long-running workload in parallel, in order to finish faster. In reality, though, this involves more than just restoring databases. And I have significant skew to deal with: one database that is many times larger than all the rest and has a higher growth rate.
2024-06-07
Once Windows Server Failover Clusters have been set up, we can set up Availability Groups in SQL Server. This article will focus on setting up Basic Always-On Availability Groups in SQL Server Standard Edition.
This facilitates High Availability in SQL Server Standard, with three levels of availability and failover:
Asynchronous commit with manual or forced failover,
Synchronous commit with manual or forced failover,
Synchronous commit with automatic failover.
2024-06-05
16,299 reads
Over the years Power BI has evolved into a complex and varied ecosystem of tools and solutions, which in its turn demands several supporting roles: there are, of course, developers, data engineers and data scientists, but there is need for one more, i.e. a capacity administrator.
2024-06-05
803 reads
A new cohort of WITspiration is strating, the women in technology mentoring circle.
2024-06-05
This article shows how to access Snowflake information from Synapse Analytics.
2024-06-03
1,747 reads
Your challenge for this week was to find out who keeps mangling the contents of the AboutMe column in the Stack Overflow database.
2024-06-03
Another article on how the SQL language works in PostgreSQL. This time we examine the UNION, INTERSECT, and EXCEPT operators.
2024-05-31
1,546 reads
Learn about the SQL Server BULK INSERT command and how to use it to import text data in a SQL Server database table.
2024-05-31
In the contemporary digital landscape, web applications play a pivotal role in delivering services and facilitating interactions between users and businesses. However, the performance of these applications heavily relies on the efficiency of underlying databases. This comprehensive study aims to explore the intricate relationship between database optimization techniques and web application performance enhancement. The study begins by delineating the significance of web application performance and its correlation with database operations. It examines various factors affecting performance, including data retrieval, storage, and processing. Furthermore, it identifies common challenges such as latency, scalability issues, and inefficient query execution. Through an extensive review of the literature, this study evaluates state-of-the-art database optimization methodologies and their applicability to web applications. Techniques such as indexing, query optimization, denormalization, caching mechanisms, and data partitioning are scrutinized, highlighting their potential to mitigate performance bottlenecks. Moreover, the study investigates emerging trends and technologies in database management systems (DBMS), such as NoSQL databases, in-memory databases, and cloud-based solutions. It assesses their suitability for enhancing web application performance, considering factors like data volume, query complexity, and real-time processing requirements.
2024-05-29
2,254 reads
How I used AI for this postChatGPT to generate images based on info specifically...
By Brian Kelley
A few months ago I started using Deepstash. Deepstash breaks books into the key...
By Brian Kelley
Do you have a case where you have a named instance you'd like to...
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The Data API Builder MCP Server, v2.x, includes a number of tools. What actions can these tools perform in your database?
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