The Evolution of SQL Server 2022

​The details around Microsoft’s launch of SQL Server 2022 are still emerging. Learning about “the most Azure-enabled iteration of SQL Server ever” is terrific news for data workers everywhere. 

​Organizations striving to deal with the exponential data surge can benefit from the latest feature additions. Relational and unstructured data that must now store at the edge, on-premises, and in the cloud continues to pose challenges. 

​“The most revolutionary firms produce predictive insights on current data, whereas others may struggle to drive even reactive insights to their past data,” according to Microsoft’s release. can compartmentalize information across divisions and geographies.” 

​Kindly keep reading to learn more about the new feature announcements, their implications for database administrators and data professionals, and my thoughts.

​From SQL Server 2022 onwards, one of the most intriguing features will be the ability to connect directly to S3. Backups will be better, and recovery times will be faster. It will also make developing, testing, and implementing analytics, big data, and AI applications easier. It is critical to assist organizations in improving the results of their analytics and AI activities. Big data and analytics data are growing quicker than structured data. Let’s look back to see how we got to this position with big data. 

Apache created Hadoop’s extensive data storage layer. The Hadoop Distributed File System was built in 2004, shortly after “big data” was used (HDFS). John Mashey, the chief scientist at Silicon Graphics International (SGI), gave a session titled “Big Data… and the Next Wave of InfraStress” at a USENIX convention in 1998. The term “big data” is said to have been coined by Mashey. He mentioned it in several of his speeches at the conference. Hadoop and MapReduce both appeared simultaneously, so the two words became interchangeable.

Hadoop and HDFS swiftly dominated the market and the attention of big data wranglers as this new scientific approach to data gained traction. A language and ecosystem with catchy names like Pig and Hive arose in space. This strategy worked well for batch processing and massive data, but combining these types with day-to-day relational data in SQL Server 2022 proved too challenging. Years before, Microsoft developers had predicted this problem and were already working on a remedy. What if we retrieved the data from the unstructured data storage place and fed it to SQL Server instead of saving it there?

Due to the problems in integrating unstructured and structured data, Microsoft created SQL Server Big Data Clusters based on HDFS to blend unstructured and structured data on the fly without necessitating significant data migration. As a result, DBAs can now provide unstructured data to SQL Server. It could query and be integrated directly from additional sources, using the same tools they used daily.

Let’s fast forward a few years from then. Data growth hasn’t slowed, and while the data types are diverse, the applications are ever-changing. With Hadoop’s continuing expansion, the batch processing that made it so dependable couldn’t keep up with the demands of the business. New players began to join the game.

Amazon introduced Simple Storage Service (S3) in 2006, and it quickly became a disruptive force. S3 provides features that data engineers prefer over HDFS, such as scalability, durability, and permanence. It has gained in popularity and market share since then. It is something that Microsoft is aware of.

Microsoft is staying true to its core ideals of meeting consumers where they are and giving them the best tools for dealing with tomorrow’s issues. SQL Server 2022 will include an S3 connection, Microsoft announced this week at Ignite 2021. In a blog post by Bob Ward, a key architect at Microsoft, you can learn more about it. He claims: “We have new extensions to the T-SQL language to support data virtualization and backup/restore with S3 compatible storage systems. “– Bob Ward, principal architect at Microsoft.

Make the connections necessary to access structured and unstructured data as significant data clusters and SQL Server grow. It must deliver the most helpful data insights with the least effort. At first glance, it appears to be a fantastic opportunity for large data clusters and networking. A link to S3 allows for quick backups and restores.
It is where things start to get complicated. Many developers would also argue that excellent S3 isn’t the same as HDFS. Microsoft Visual Studio Code is not the same as Server Manager, as any software engineering student will tell you (SSMS). HDFS is a storage platform that you manage and run on your own. As part of the HDFS experience, you’re responsible for handling, scaling, and coping with node failures. S3 and a unified fast file and object (UFFO) technology like Pure Storage FlashBlade overcome these problems.

The data future is rapidly evolving. Having additional persistent storage solutions that limit ransomware threats with built-in safeguards like SafeModeTM snapshots provides you the extra peace of mind to confidently move forward gives you the extra peace of mind to confidently move forward. Also, the S3 option speeds up the data flow from SQL Server 2022. As we continue to develop solutions with relational and unstructured data, AI will reduce connection friction. It’s fantastic to see Microsoft’s SQL Server ecosystem continue to grow. Pure Storage will continue developing and offering value-added connectors and storage solutions to assist SQL Server 2022 users in getting the most out of their data.