Microsoft is excited to announce a new preview for the next version of SQL Server! We disclosed a name for this next release, SQL Server 2017, today at the Microsoft Data Amp event. Community Technology Preview (CTP) 2.0 is the first production-quality preview of SQL Server 2017, and it is available on both Windows and Linux. In this preview, we added a number of new capabilities, including the ability to run advanced analytics using Python in a parallelized and highly scalable way, the ability to store and analyze graph data, and other capabilities that help you manage SQL Server for high performance and uptime, including the Adaptive Query Processing family of intelligent database features and resumable online indexing.
In addition to all these great new features we are excited to announce a world record in the TPC-H 1TB data warehousing workload (non-clustered). The benchmark was achieved with SQL Server 2017 on Red Hat Enterprise Linux and HPE Prolliant server hardware, beating SQL Server 2016 on the same hardware handily. This is just the first of many anticipated performance benchmarks for SQL Server 2017 on Linux and Windows, demonstrating SQL Server’s industry leading performance. When taken in conjunction with the fact that SQL Server has had the least vulnerabilities of any major database over the last 7 years in the National Institute of Standards and Technology (NIST) vulnerability database, SQL Server 2017 on Windows and Linux is the best database for your Mission Critical application and data warehouse workloads.
You can try the preview in your choice of development and test environments now.
Key CTP 2.0 enhancements on Windows and Linux
We also added support for storing and analyzing graph data relationships. This includes full CRUD support to create nodes and edges and T-SQL query language extensions to provide multi-hop navigation using join-free pattern matching. In addition, SQL Server engine integration enables querying across SQL tables and graph data. And, you can use all of your existing SQL Server tools to work with graph data.
With resumable online index rebuild, you can resume a paused index rebuild operation from where the rebuild operation was paused rather than having to restart the operation at the beginning. Additionally, this feature rebuilds indexes using only a small amount of log space. This feature will help pick up right where you left off when an index maintenance job encounters issues, or allow you to split index rebuilds across maintenance windows.
New in SQL Server 2017, we’re adding the Adaptive Query Processing family of intelligent database features. These features automatically keep database queries running as efficiently as possible without requiring additional tuning from database administrators. In addition to the previous capability to adjust batch mode memory grants, in CTP 2.0 Adaptive Query Processing adds the batch mode adaptive joins and interleaved execution capabilities. Interleaved execution will improve the performance of queries that reference multi-statement table valued functions by surfacing runtime row counts to the query optimizer. Batch mode adaptive joins enables the choice of a query’s physical join algorithm to be deferred until actual query execution, improving performance based on runtime conditions.
In addition, some functionality that was previously available in SQL Server on Windows is now available on Linux for the first time. This includes:
- Additional SQL Server Agent capabilities – Use SQL Server Agent to keep replicas in synch with log shipping.
- Listener for Always On availability groups – The listener enables clients to connect to the primary replica in an availability group, monitoring availability and directing connections to the replicas.
Key CTP 2.0 enhancement to SQL Server on Windows – Python for analytics
Another new, key feature enhancement in CTP 2.0 of SQL Server 2017 is the ability to run the Python language in-database to scale and accelerate machine learning, predictive analytics and data science scripts. The new capability, called Microsoft Machine Learning Services, enables Python scripts to be run directly within the database server, or to be embedded into T-SQL scripts, where they can be easily deployed to the database as stored procedures and easily called from SQL client applications by stored procedure call. SQL Server 2017 will also extend Python’s performance and scale by providing a selection of parallelized algorithms that accelerate data transforms, statistical tests and analytics algorithms. This functionality and the ability to run R in-database and at scale are only available on Windows Server operating system at this time.
Get SQL Server 2017 CTP 2.0 today!
Get started with the preview of SQL Server with our developer tutorials that show you how to install and use SQL Server 2017 on macOS, Docker, Windows, and Linux and quickly build an app in a programming language of your choice.
- Register to attend an Engineering Town Hall about “Security in SQL Server on Linux”
- Install on Red Hat Enterprise Linux
- Install on Ubuntu Linux
- Install on SUSE Linux Enterprise Server
- Pull and run a Linux Docker container
- Download the preview for Windows
- Create a SQL Server on Linux virtual machine in Azure
- Sign up for the Early Adoption Program (EAP) – The Early Adoption Program is designed to help customers and partners evaluate new features in SQL Server2017 and to build and deploy applications for SQL Server 2017 on Windows and Linux.