Once again, SQL Server 2017 has led the pack with three new TPC benchmarks published in April 2019, ranking SQL Server 2017 as the fastest database for online transaction processing (OLTP) and data warehouse (DW) workloads on Windows and Linux.
Together with our partners, SQL Server continues to innovate with high-performing, enterprise-ready solutions that deliver unparalleled price performance. Were pleased to share the results for the TPC-H (the industry standard for benchmarking data warehouse) performance at 3TB with HPE that currently holds the record as the industrys fastest 2-socket non-clustered solution, and 10TB with Cisco, as well as the TPC-E (the industry standard for benchmarking online transaction processing) performance at 10TB with Lenovo. Check out the results below.
System Performance Database Operating System HPE Proliant DL380 Gen10
SQL Server 2017 Enterprise Edition
SUSE Linux Enterprise Server 15
Cisco UCS C480 M5 Server
SQL Server 2017 Enterprise Edition
Red Hat Enterprise Linux 7.6
The table above shows the TPC-H data warehousing results published on SQL Server 2017 with configuration
You love data. You love the way it helps you and your organization make better decisions. You love the way it creates real insight into trends that are shaping our world. Plus, data is just plain cool; whats not to love about that?
We love data too. Thats why were excited #SQLDataWins is running for a second year! #SQLDataWins is a sweepstakes that celebrates data and your ability to use it in solving problems and helping your organization grow. Starting May 13th, youll help us complete some memes we can all relate to for a chance to win great swag.
Visit @SQLServer every Monday for the next four weeks to check out a new meme and select the answer that you think fits best. Tweet your response no later than 11:59 PM Pacific Time on Thursday each week. Be sure to use the handy auto-generated tweet, including #SQLDataWins and the original image, for a chance to win.
Hot tip: Check back every week for a new meme!
FAQs How do I enter?
Its easy! Follow these three simple steps by Thursday at 11:59 p.m. Pacific Time:
Visit SQL Server on Twitter. Find this weeks #SQLDataWins meme (hint: it will
https://cloudblogs.microsoft.com/sqlserver/2019/05/08/the-may-release-of-azure-data-studio-is-now-available/Source: https://cloudblogs.microsoft.com/sqlserver/2019/05/08/the-may-release-of-azure-data-studio-is-now-available/ Were excited to announce the May release of Azure Data Studio (formerly known as SQL Operations Studio) is now available. You can download Azure Data Studioand review the release notes to get started. Please note: After READ MORE
When I joined the SQL Tools team as a PM back in October 2018, my top priority was to release SQL Server Management Studio (SSMS) 18. I expected a fair amount of work but didnt realize how complicated the process would be. 6 months later, having passed several internal checks such as accessibility, privacy, security, compliance, etc. among many others, and after 5 previews, I am very excited to share that SSMS 18 is now generally available. You can download SQL Server Management Studio 18 today.
Its been a long journey. We were very close to getting the release out multiple times, until some ship blocker showed up at the last minute and we had to bail. Ideally, we want to ship a product thats better than the version its replacing.
My work is not done but has just begun. We will continue to bring cool features into both SQL Server Management Studio as well as Azure Data Studio as it makes sense.
Some of you may have been following the journey, and some not. For the sake of completeness, as well as to recognize all the fantastic work the SSMS team has done, Id like to highlight all
Were excited to announce the monthly release of SQL Server 2019 community technology preview (CTP) 2.5. SQL Server 2019 is the first release of SQL Server to closely integrate Apache Spark and the Hadoop Distributed File System (HDFS) with SQL Server in a unified data platform.
The CTP 2.5 preview brings the following new features and capabilities to SQL Server 2019:
Big data clusters For more control and flexibility over the big data cluster layout and configuration settings, were introducing a new deployment mechanism that uses configuration files to deploy your cluster. You can start from the built-in configurations that come with the mssqlctl utility and customize them to accommodate the platform you want to run the big data cluster on. To streamline the deployment process, mssqlctl utility enables an interactive deployment experience that guides you through the steps to initiate the deployment with prompts for required inputs. You can also automate the entire process using mssqlctl configuration commands available to list, customize, or deploy using configuration files. To avoid incompatibilities between client utility and big data cluster server versions, you can now verify you installed the right version of the utility by using mssqlctl –version command. The new
https://cloudblogs.microsoft.com/sqlserver/2019/04/18/the-april-release-of-azure-data-studio-is-now-available/Source: https://cloudblogs.microsoft.com/sqlserver/2019/04/18/the-april-release-of-azure-data-studio-is-now-available/ We are excited to announce the April release of Azure Data Studio (formerly known as SQL Operations Studio) is now available. Download Azure Data Studioand review the Release notes to get started. Please note: After downloading READ MORE
This post was co-authored by Jeff Shepherd, Deepak Mukunthu, and Vijay Aski.
Recently, we blogged about performing automated machine learning on SQL Server 2019 big data clusters. In todays post, we will present a complementary automated machine learning approach leveraging Azure Machine Learning service (Azure ML) invoked from SQL Server. While the previous post dealt with a Spark-based implementation tuned for big data, this post presents an approach that runs directly in SQL Server running on a single server. This is well suited for use with data residing in SQL Server tables and provides an ideal solution for any version of SQL Server that supports SQL Server Machine Learning Services.
Azure Machine Learning service
Azure Machine Learning service is a cloud service. We call the service from SQL Server to manage and direct the automated training of machine learning models in SQL Server. Automated machine learning tries a variety of machine learning pipelines. It chooses the pipelines using its own machine learning model based on the scores from previous pipelines. Automated machine learning can be used from SQL Server Machine Learning Services, python environments such as Jupyter notebooks and Azure notebooks, Azure Databricks, and Power BI.
Starting in SQL Server
Businesses today are faced with the challenge of staying profitable and investing in future innovations. Speed and flexibility are the name of the game, and effective data-scaling techniques are highly sought after. Yet exploding data volumes, diverse data types, and numerous database management systems make it harder than ever for data professionals to consolidate data and synthesize key business insights.
SQL Server 2019 big data clusters simplify security, deployment, and management of all of your key data workloads and data lakes, while including innovative security and compliance features, industry-leading performance, and mission-critical availability of the platform.
In this webinar I will join Travis Wright, Principal Program Manager at Microsoft to demonstrate how to simplify big data to make faster and better business decisions with the new SQL Server 2019 big data clusters feature. Learn more about how the latest edition has evolved beyond your grandfather’s SQL Server to a unified data platform that includes distribution for Hadoop, Apache Spark, and AI. Attend ready to learn about:
Using data virtualization, integrate, query, and retrieve all of your data from relational, non-relational, or unstructured data sourcesincluding big datawithout replicating or moving the data. Easily manage all of this data with a
Were delighted to release the Azure Toolkit for IntelliJ support for SQL Server Big Data Cluster Spark job development and submission. For first-time Spark developers, it can often be hard to get started and build their first application, with long and tedious development cycles in the integrated development environment (IDE). This toolkit empowers new users to get started with Spark in just a few minutes. Experienced Spark developers also find it faster and easier to iterate their development cycle.
The toolkit extends IntelliJ support for the Spark job life cycle starting from creation, authoring, and debugging, through submission of jobs to SQL Server Big DataClusters. Itenables you to enjoy a native Scala and Java Spark application development experience and quickly start a project using built-in templates and sample code. The integration with SQL Server Big Data Cluster empowers you to quickly submit a job to the big data cluster as well as monitor its progress. The Spark console allows you to check schemas, preview data, and validate your code logic in a shell-like environment while you can develop Spark batch jobs within the same toolkit.
The Azure Toolkit for IntelliJ offers the following capabilities:
Connect to SQL Server Big
https://blogs.msdn.microsoft.com/sqlsecurity/2019/03/29/we-have-moved/Source: https://blogs.msdn.microsoft.com/sqlsecurity/2019/03/29/we-have-moved/ Thanks for visiting! This blog has now been migrated to: https://techcommunity.microsoft.com/t5/Azure-SQL-Database/bg-p/Azure-SQL-Database/label-name/SQLServerSecurity