Are you curious how new capabilities in SQL Server will impact your applications? Download and test SQL Server 2017 Developer Edition, a full-featured free edition, licensed for use as a development and test database in a non-production environment. You can browse and access SQL Server code samples at GitHub, and when youre ready, check out your options to move to production.
With SQL Server 2017, you can build modern applications using the language of your choice, on-premises or in the cloud, on Windows, Linux, and Docker containers. Your mission-critical programs will benefit from industry-leading scalability, performance, and availability. And SQL Server 2017 is the only commercial database with AI built-in, enabling you to build intelligent applications using scalable and highly parallelized R and Python. Read the datasheet and white paper for more details.
If youre a Linux developer, SQL Server 2017 brings the database you want to the platform you loveand dont just take our word for it. Browse technical FAQs from your peers in our quick start guide.
SQL Server 2017 Developer Edition does not include a licensed OS, such as a license for Windows 10 included on a new laptop. 90 to 180 day free trials of Windows
Modern enterprises are struggling to gain insights from an exploding number of database management systems and ever-growing data volumes. SQL Server 2019 can help you overcome the challenges of integrating data and bring AI and machine learning to all of your data, structured and unstructured. It can also help you better manage your relational data right now.
In this webinar, Introduction to SQL Server 2019, hear from Debbi Lyons, Senior Product Marketing Manager, Travis Wright, Principal Program Manager, and Bob Ward, Principal Architect at Microsoft discuss the latest updates and features for the new SQL Server release, including introducing the new big data cluster with intelligence over any data, how SQL Server 2019 enhances the developer experience, and using tools including Azure Data Studio.
Listen to the webinar on-demand to learn more about whats new in SQL Server 2019, including how to:
Access and manage all data structured and unstructured conveniently from one place
With SQL Server 2019 big data clusters, Apache SparkTM and HDFS are packaged together with SQL Server as a single, integrated solution. In the webinar, you can watch a demo of the unified platform and see how Azure Data Studio is integrated
https://blogs.msdn.microsoft.com/sql_server_team/lets-talk-about-trace-flags/Source: https://blogs.msdn.microsoft.com/sql_server_team/lets-talk-about-trace-flags/ One of the most confusing aspects of SQL Server configuration is often trace flags. There are lots of trace flags out there, and while many of them are documented, when to use them and when not to READ MORE
https://blogs.msdn.microsoft.com/sql_server_team/replica-failover-within-the-secondary-availability-group-in-a-distributed-availability-group/Source: https://blogs.msdn.microsoft.com/sql_server_team/replica-failover-within-the-secondary-availability-group-in-a-distributed-availability-group/ A distributed availability group (DAG) is a special type of availability group that spans two availability groups. This blog will clarify some issues regarding failover in a DAG. A simple DAG ‘TIWENDAG’ is created for relevant tests READ MORE
We are excited to announce the January release of Azure Data Studio (formerly known as SQL Operations Studio) is now available.
Note: If you are currently using the preview version, SQL Operations Studio, and would like to retain your settings when upgrading to the latest version, please follow these instructions. After downloading Azure Data Studio, click “Yes” to enable preview features so that you can use extensions.
Azure Data Studio is a new cross-platform desktop environment for data professionals using the family of on-premise and cloud data platforms on Windows, MacOS, and Linux. To learn more, visit our GitHub.
Azure Data Studio was announced Generally Available at Microsoft Ignite 2018. If you missed it, you can view that GA announcement here. You wont want to miss the great orthogonality matrix that compares SQL Server Management Studio (SSMS) and Azure Data Studio, and it may provide answers to many of your questions.
Check out the video below for a general overview of Azure Data Studio.
The key highlights for the January release include:
Azure Active Directory Authentication support Announcing Data-Tier Application Wizard support Announcing IDERA SQL DM Performance
In this post, we will explore how to use automated machine learning (AutoML) to create new machine learning models over your data in SQL Server 2019 big data clusters.
SQL Server 2019 big data clusters make it possible to use the software of your choice to fit machine learning models on big data and use those models to perform scoring. In fact, Apache SparkTM, the popular open source big data framework, is now built in! Apache SparkTM includes the MLlib Machine Learning Library, and the open source community has developed a wealth of additional packages that integrate with and extend Apache SparkTM and MLlib.
Automated machine learning
Manually selecting and tuning machine learning models requires familiarity with a variety of model types and can be laborious and time-consuming. Software for automating this process has recently become available, relieving both novice and expert Data Scientists and ML Engineers of much of the burden that comes with manual model selection and tuning.
H2Os open source AutoML APIs
H2O provides popular open source software for data science and machine learning on big data, including Apache SparkTM integration. It provides two open source python AutoML classes: h2o.automl.H2OAutoML and pysparkling.ml.H2OAutoML. Both APIs use the same
Companies today demand the latest innovations for every solution they deliver. How can you make sure your infrastructure and data estate keep up with the demands of your business? Read the tips below, and join our upcoming webinar on transforming your business with a modern data estate.
1. Prioritize data
Data is at the core of modern applications. Two key trends that help organizations extract the most from their data are:
The adoption of cloud technologies and The ability to reason through any data with artificial intelligence (AI)
Organizations that modernize and harness cloud, data, and AI can outperform their competition and become leaders in their fields.
Microsoft understands the importance of maintaining a modern data estate. Tools like the new Azure Database Migration Service empower you to seamlessly migrate from a wide-range of data sources to Azure with near-zero application downtime. If you have a large number of databases, consider migrating to Azure SQL Database Managed Instance, a fully managed PaaS solution that has full compatibility with SQL Server, back to version 2005. This enables a true lift-and-shift of legacy SQL Server installations to Azure with few or no application code changes.
2. Make cost-effective choices
We are very excited to announce the Public Preview 6 of SQL Server Management Studio (SSMS) 18.0. In the spirit of more frequent releases, Preview 6 brings another incremental update to SSMS 18.0. This release has new features and capabilities, several bug fixes across SQL Server Management Objects (SMO), intelliSense improvements in UI, etc.
As your on-premise SQL Server 2008 and SQL Server 2008 R2 installations approach their end of life support, are you looking for ways to modernize your database environments by migrating to Azure? If so, consider the following:
Typically, you first want to assess your on-premise databases to identify any potential SQL Server features and/or compatibility issues that can impact database functionality after you move to the newer version of SQL Server, Azure SQL Database, or Azure SQL Database Managed Instance. Next, you should plan for any needed fixes that you will need to accommodate in your target Azure Database platform after migration, as recommended by the Data Migration Assistant (DMA), and then you are ready to migrate your databases to Azure.
In Preview 6 of SQL Server Management Studio
With the first public preview of SQL Server 2019, we announced support for the widely used UTF-8 character encoding as an import or export encoding, and as database-level or column-level collation for string data.This is an asset for companies extending their businesses to a global scale, where the requirement of providing global multilingual database applications and services is critical to meet customer demands, and specific market regulations. The benefits of introducing UTF-8 support extend to scenarios where legacy applications require internationalization and use inline queries: the amount of changes and testing involved to convert an application and underlying database to UTF-16 can be costly, by requiring complex string processing logic that affect application performance.
To limit the amount of changes required for the above scenarios, UTF-8 is enabled in existing the data types CHAR and VARCHAR. String data is automatically encoded to UTF-8 when creating or changing an objects collation to a collation with the UTF8 suffix, for example from LATIN1_GENERAL_100_CI_AS_SC to LATIN1_GENERAL_100_CI_AS_SC_UTF8. Refer to Set or Change the Database Collation and Set or Change the Column Collation for more details on how to perform those changes. NCHAR and NVARCHAR remain unchanged and only allow UTF-16 encoding.
UTF-8 is only
SQL Server 2019 preview brings encryption technology to a broader set of scenarios by enabling rich confidential computing capabilities with the enhanced Always Encrypted feature, Always Encrypted with secure enclaves. Always Encrypted with secure enclaves allows rich computations on encrypted data, boosts performance when encrypting large columns of data or complex schemas, and enables customers to protect sensitive Personally Identifiable Information (PII) data when running rich queries.
Always Encrypted debuted in SQL Server 2016 as a solution for protecting sensitive data used during the processing of Transact-SQL queries. With Always Encrypted, the data is encrypted and decrypted on the client-side, and is not exposed in plaintext in memory of the SQL Server process. As a result, even DBAs and administrators of machines hosting the database can’t see plaintext data. This makes Always Encrypted a great way to keep your data secure, but it restricts computations that SQL Server can perform on the data.
The only operation SQL Server 2016 and 2017 support on encrypted database columns is equality comparison, providing you use deterministic encryption. For anything else, your apps need to download the data to perform the computations outside of the database. Similarly, if you need to encrypt your data