About Me

I now work for Microsoft Federal in Chevy Chase, MD.

Dedicated to providing customer-driven, results-focused solutions to the complex business problems of today... and tomorrow.

At SQLTrainer.com, LLC  we understand that the technical challenges faced by businesses today are much greater in both scope and complexity than they have ever been. Businesses today are faced with understanding both local IT infrastructures as well as cloud-based technologies.

What is SQLTrainer.com?

Founded in 1998 by Ted Malone, SQLTrainer.com is a technical consulting, training and content development firm dedicated to the following core principles:

  • Technology Alone is NOT the Answer! - Implementing a particular technology because it is interesting or "cool" will not solve customer problems.
  • Technology Solutions do NOT need to be Overly Complex! - Many times developers and technical practitioners will attempt to build the most clever solution possible. While this serves to stroke the egos of those involved, it doesn't provide a maintainable solution.
  • Consultants Should be Mentors First! - When looking to hire an external consultant, businesses should look to the consultant who's willing to train themselves out of a paycheck.

Why the name, SQLTrainer.com?

SQL (pronounced See-Quell) stands for Structured Query Language, which is at the heart of every modern-day relational database system. Since many technology solutions today rely on some form of database storage or interaction, it was only logical to find a way to incorporate SQL into the name of the organization. Given that one of our core principles is to be a mentor/training above everything, the name SQLTrainer made sense. Since we also wanted to represent our embracing of the cloud, it seemed logical to add the ".com", referring to the biggest "cloud" of them all.

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Wednesday, June 24, 2015 11:00:00 AM

From Tiffany Wissner, Senior Director, Data Platform

In the SQL Server CTP 2 blog, T.K. Ranga Rengarajan, CVP of SQL Server engineering, discussed bringing cloud first innovations to SQL Server 2016. This includes a rapid preview model that exists in Microsoft Azure today.  With the release of SQL Server 2016 Community Technology Preview (CTP) 2.1, for the first time customers can experience the rapid preview model for their on-premises SQL Server 2016 development and test environments.  This born in the cloud model means customers don’t have to wait for traditional CTPs that are released after several months for the latest updates from Microsoft engineering, and can gain a faster time to production.  The frequent updates are also engineered to be of the same quality as traditional major CTPs, so customers don’t have to be concerned about build quality.  In addition, customers have the flexibility to choose which CTP they will deploy for the development and test environment and are not forced to upgrade to the most recent preview release. 

In SQL Server 2016 CTP 2.1, available for download today, customers will see improvements to the Stretch Database technology released in CTP 2, along with improvements to the Query Store, Temporal Database and in-memory columnstore.  To learn more about the specific improvements for each feature please view the SQL Server 2016 Community Technology Preview 2.1 blog.

In addition to the new CTP model, SQL Server Management Studio (SSMS) is now being offered as a stand-alone install outside of the SQL Server release.  This means Azure SQL database customers can use SSMS for the new features being released in cloud as well as their on-premises SQL Server.  SSMS as a standalone tool will also follow the rapid preview model with frequent updates to keep pace with the new features being released in Azure SQL Database.  You can download the first Preview release of the standalone SQL Server Management Studio (SSMS) June 2015 Preview, here. To learn more about the features included please take a look at SQL Server Management Studio June 2015 Release Blog.

Download SQL Server 2016 CTP 2.1 preview today!

As the foundation of our end-to-end data platform, with this release we continue to make it easier for customers to maximize their data dividends. With SQL Server 2016 you can capture, transform, and analyze any data, of any size, at any scale, in its native format —using the tools, languages and frameworks you know and want in a trusted environment on-premises and in the cloud.

To learn more about the release, visit the SQL Server 2016 preview page.  To experience the new, exciting features in SQL Server 2016 and the new rapid release model in place download the preview or trial the preview using a virtual machine in Microsoft Azure and start evaluating the impact these new innovations can have for your business.  Also, be sure to share your feedback on the new SQL Server 2016 capabilities using Microsoft’s Connect tool.  We look forward to hearing from you!

Wednesday, June 24, 2015 11:00:00 AM

Following the release of SQL Server 2016 CTP 2.0 last month, the SQL Server engineering team is excited to announce the immediate availability of CTP 2.1 release for download. The release includes improvements for three new innovations releasing in SQL Server 2016 - Stretch Database, Query Store, Temporal - and Columnstore Index, introduced in SQL Server 2012:

  1. Stretch Database, which enables transparent stretching of warm and cold OLTP data to Microsoft Azure in a secure manner without requiring any application changes, includes the following fixes:
    1. Data migration does not trigger lock escalation in stretched tables, so no timeouts for INSERT or SELECT operations
    2. Automatic encryption and validation requirement of remote server certification, preventing “man-in-the-middle” security attacks
    3. Ability to run INSERT statement against updatable views created on top of stretch tables
  2. Query Store, the “flight recorder” which stores historical query plans and their performance characteristics, allowing DBAs to monitor and analyze plans and force a specific query plan on regression, includes:
    1. Parse statistics avg_parse_duration, last_parse_duration, avg_parse_cpu_time, last_parse_cpu_time removed from sys.query_store_query view
    2. The minimally allowed for flush_interval_seconds parameter, 60 seconds, is now verified in ALTER DATABASE statement
    3. Naming in sys.database_query_store_options and actual parameters in ALTER statements are in alignment with flush_interval_seconds and operation_mode
    4. Query Store on master and tempdb disabled and error message thrown ("Cannot perform action because Query Store cannot be enabled on system database master (tempdb)")
    5. Force_failure_count parameter is now cleared after plan is enforced
  3. Temporal, which enables handling and analyzing database records that changes over time, includes:
    1. Support for computed columns
    2. Support for marking one or both period columns with HIDDEN flag, allowing for frictionless migration for existing applications. The following applies to HIDDEN period columns:
        1. Column is not returned in SELECT * statements
        2. INSERT statement without column list do not expect inputs for HIDDEN columns
        3. Hidden column must be explicitly included in all queries that directly reference temporal table or other objects that reference temporal table (views, for example)
        4. BULK INSERT scripts that worked with non-temporal table (prior to adding system-versioning and hidden period columns) will continue to work and hidden columns will be auto-populated
        5. is_hidden flag is set to 1 in sys.columns view

  4. Columnstore Index includes:
    1. Improved seek performance
    2. Improved scan performance with partitioned tables

 

 

Wednesday, June 24, 2015 10:30:00 AM

By Tiffany Wissner, Senior Director, Data Platform

At the Build conference in April, we announced Azure SQL Data Warehouse, our new enterprise-class elastic data warehouse-as-a-service. Today, we’re pleased to announce that Azure SQL Data Warehouse is open for Limited Public Preview.  

With growing data volumes, you have been telling us that you want to take advantage of the cost-efficiencies, elasticity and hyper-scale of cloud for your large data warehouses. You also need for that data warehouse to work with your existing infrastructure and tools, utilize your current skills and integrate with many sources of data. With Azure SQL Data Warehouse, we deliver:

  • The first enterprise-class elastic data warehouse that includes the separation of compute and storage, enabling customers to pay for what they need, when they need it
  • The ability to pause the database  so you only pay for commodity storage costs
  • Full SQL Server experience that includes PolyBase that allows you to combine queries for your structured and unstructured data using the skills you have today  
  • Hybrid options – your data, your platform, your choice

Azure SQL Data Warehouse is based on SQL Server’s massively parallel processing architecture currently available only in the Analytics Platform System (APS), and integrates with existing data tools including Power BI for data visualization, Azure Machine Learning for advanced analytics, Azure Data Factory for event processing and Azure HDInsight, Microsoft’s 100% Apache Hadoop managed big data service.

First enterprise-class elastic cloud data warehouse

This is the first elastic cloud data warehouse to offer enterprise class features our customers and partners expect and need like full indexing, stored procedure/functions, partitions, and columnar indexing. Without these features, organizations have to rewrite their existing applications and workflows at significant cost and slower time to market. This is the first fully managed cloud data warehouse to offer the compatibility SQL users need to migrate to the cloud.  Azure SQL Data Warehouse will be supported by a rich ecosystem of partners that support SQL Server today. Find out more about the partners we are working with from Garth Fort, GM of the enterprise partner group at Microsoft here.

And, because Azure SQL Data Warehouse independently scales compute and storage, users only pay for query performance as they need it.  Unlike other cloud data warehouses that require hours or days to resize, the service allows customers to grow or shrink query power in seconds. As you can scale compute costs separately from storage costs, costs are easier to forecast than competitive offerings.

Pause compute for lower costs

Elastic pause enables a customer to shut down the compute infrastructure while persisting the data and only paying for data storage. Customers can schedule pausing compute usage either through Azure SQL Data Warehouse or Azure Scheduler to optimize the cost of the service.

Leveraging existing SQL server skills with Hadoop

With the incredible growth of all types of data, the need to combine structured and unstructured data is essential. With Polybase, we offer the ability to combine data sets easily. SQL Data Warehouse can query semi-structured data stored in blob storage using familiar T-SQL, making it easy to gain insights from various data types.

Hybrid data warehouse – your data, your platform, your choice

Deploying on-premises data warehouse solutions can range from weeks to months. Azure SQL Data Warehouse takes seconds to provision. Cloud born data is more readily ingested into Azure SQL Data Warehouse. Other technologies such as Azure Data Factory and Power BI, which is available as a Connector to Azure SQL Data Warehouse today, provide the data management gateway which makes bringing data from on-premises sources to the cloud much simpler.  Azure SQL Data Warehouse also uses the same management as APS appliance to make hybrid management easier. 

 

One of the use cases for SQL Data Warehouse is the ability to cost effectively explore new insights and analytical workloads without impacting production platforms. This enables customers and partners to engage in new development and testing scenarios, based on real world requirements without the overhead production supportability and management constraints. 

The initial public preview is designed for data warehouses in the 5-10 TB range to give users the ability to start testing and providing feedback on the service. You can sign up now, and as we ramp the preview, new customers will be notified as they are accepted.

As with this Azure SQL Data Warehouse release, we continue to make it easier for customers to maximize their data dividends.  With our data platform you can capture, transform, and analyze any data, of any size, at any scale, in its native format —using the tools, languages and frameworks you know and want in a trusted environment on-premises and in the cloud.

To learn more about Azure SQL Data Warehouse and sign-up for the Public Preview, click here.

Wednesday, June 10, 2015 6:00:00 AM

Microsoft is committed to continuous innovation to make Azure the best cloud platform for running hyper-scale big data projects. This includes an existing Hadoop-as-a-service solution, Azure HDInsight, a hyper-scale repository for big data, Azure Data Lake, and Hadoop infrastructure-as-a-service offerings from Hortonworks and Cloudera. This week, Hortonworks also announced their most recent milestone with Hortonworks Data Platform 2.3 which will be available on Azure this summer.

Today, we are excited to announce that MapR will also be available in the summer as an option for customers to deploy Hadoop from the Azure Marketplace. MapR is a leader in the Hadoop community that offers the MapR Distribution including Hadoop which includes MapR-FS, an HDFS and POSIX compliant file store, and MapR-DB, a NoSQL key value store. The Distribution also includes core Hadoop projects such as Hive, Impala, SparkSQL, and Drill, and MapR Control System, a comprehensive management system. When MapR is available in the Azure Marketplace, customers will be able to launch a full Hadoop cluster based on MapR as an Azure Virtual Machine with a few clicks. Together with Azure Data Lake, SQL Server, and Power BI, this will allow organizations to build big data solutions quickly and easily by using the best of Microsoft and MapR. 

Our partnership with MapR allows customers to use the Hadoop distribution of their choice while getting the cloud benefits of Azure. It is also a sign of our continued commitment to make Hadoop more accessible to customers by supporting the ability to run big data workloads anywhere – on hosted VM’s and managed services in the public cloud, on-premises or in hybrid scenarios.

We are very excited be on this journey of making big data more readily accessible to accelerate ubiquitous adoption.  We hope you join us for this ride!

T.K. “Ranga” Rengarajan

Corporate Vice President, Data Platform at Microsoft

Tuesday, June 9, 2015 10:00:00 AM

Guest post by Rohit Bakhshi, Product Manager at Hortonworks Inc.

Over the past two quarters, Hortonworks has been able to attract over 200 new customers.  We are feeding the hunger our customers have shown for Open Enterprise Hadoop over the past two years.  We are seeing truly transformational business outcomes delivered through the use of Hadoop across all industries.  The most prominent use cases are focused on:

  • Data Center Optimization – keeping 100% of the data at up to 1/100th of the cost while enriching traditional data warehouse analytics
  • 360° View of Customers, Products, and Supply Chains
  • Predictive Analytics – delivering behavioral insight, preventative maintenance, and resource optimization
  •  Data Discovery – exploring datasets, uncovering new findings, and operationalizing insights

What we have consistently heard from our customers and partners, as they adopt Hadoop, is that they would like Hortonworks to focus our engineering activities on three key themes: Ease of Use, Enterprise Readiness, and Simplification.  During the first half of 2015, we have made significant progress on each of these themes and we are ready to share what we’ve done thus far.  Keep in mind there is much more work to be done here and we plan on continuing our efforts throughout the remainder of 2015.

This week Hortonworks proudly announced Hortonworks Data Platform (HDP)  2.3  - which delivers a new breakthrough user experience along with increased enterprise readiness across security, governance, and operations. HDP 2.3 will simultaneously be available on Windows Server and Linux, and will be supported for deployment on Azure Infrastructure as a Service (IaaS) virtual machines.

In addition, we are offering an enhancement to our support subscription called Hortonworks Smartsense™.

Breakthrough User Experience

HDP 2.3 eliminates much of the complexity administering Hadoop and improves developer productivity. We employ a truly Open Source and Open Community approach with Apache Ambari to put a new face on Hadoop for the administrator, developer, and data architect.

 We actually started this effort with the introduction of Ambari 1.7.0 which delivered an underlying framework to support the development of new web-based Views.  Now, we would like to share with you some of the progress we’ve made leveraging that framework to deliver a breakthrough user experience for both cluster administrators and developers.

Enabling the Data Worker

With HDP 2.3 we focus on the SQL developer and provide an integrated experience that allows for SQL query building, displaying a visual “explain plan”, and allowing for an extended debugging experience when using the Tez execution engine.  A screenshot of what we’ve developed shown below:

With the Hive View in Ambari, developers now have a web based tool to develop, debug and interact with remote clusters in Azure. Ambari’s web based tooling allows admins to securely and easily manage their clusters on Azure without having to log in and edit configuration files on the remote cluster.

In addition to the SQL builder, we are providing a Pig Latin Editor which brings a modern browser-based IDE experience to Pig, as well as a File Browser for loading file datasets into HDFS.

HDP 2.3 brings an entirely new user experience for Apache Falcon, our Data Lifecycle Management component. The new Falcon UI allows you to search and browse processes that have executed, visualize lineage and setup mirroring jobs to replicate files between clusters and cloud storage - allowing enterprises to seamlessly backup data to Azure Blob Storage.

Smart Configuration

For the Hadoop Operator, we provide Smart Configuration for HDFS, YARN, HBase, and Hive. This entirely new user experience within Ambari is guided and more digestible than ever before. 

Shown below is the new configuration panel for Hive:

 

YARN Capacity Scheduler

The YARN Capacity Scheduler provides workload management across application types and tenants in a shared HDP cluster. HDP 2.3 delivers a  new experience to configuring workload management policies.

Ambari Web based tooling allows admins to securely and easily manage their clusters on Azure without having to log in and edit configuration files on the remote cluster.

Customizable Dashboards

In HDP 2.3 we have developed customizable dashboards for a number of the most frequently used components.  This allows for each customer to develop a tailored experience for their environment and decide which metrics they care about most.  Shown below is the HDFS Dashboard:

Enterprise Readiness: Enhancements to Security, Governance, and Operations

HDP 2.3 delivers new encryption of data-at-rest, extends the data governance initiative with Apache Atlas, and drives forward operational simplification for both on-premise and cloud-based deployments.

This release expands the fault tolerance capabilities of the platform to withstand failures - with high availability configuration options for Apache Storm, Apache Ranger, and Apache Falcon that power many mission critical applications and services.

In HDP 2.3, a number of significant security enhancements are being delivered.  The first of which is the HDFS Transparent Data at Rest Encryption.  This is a critical feature for Hadoop and we have been performing extensive testing as part of an extended technical preview.  As part of providing support for HDFS Transparent Data at Rest Encryption, Apache Ranger provides a key management service (KMS) that leverages the Key Management Provider API and can be directly leveraged to provide a central key service for Hadoop.  There is more work to be done related to encrypting data at rest, but we have confidence that a core set of use cases are ready for customers to adopt and we will continue to expand the capabilities and eliminate a variety of limitations over the coming months.

Other important additions related to Apache Ranger included providing centralized authorization for Apache Solr and Apache Kafka.  Security administrators can now define and manage security policies and capture security audit information for HDFS, Hive, HBase, Knox, and Storm along with Solr and Kafka.

Shifting to data governance, we launched the Data Governance Initiative (DGI) in January of 2015 and then delivered the first set of technology along with an incubator proposal to the Apache Software Foundation in April.  Now the core set of metadata services are being delivered along with HDP 2.3.  This is really the first step on a journey to address data governance in a holistic way for Hadoop.  Some of the initial capabilities will ease data discovery with a focus on Hive and establish a strong foundation for the future feature additions as we look to tackle Kafka, Storm, and integrating dynamic security policies based on the available metadata tags.

In addition to the new user interface elements described earlier, Apache Falcon enables Apache Hive database replication in HDP 2.3.  Previously, Falcon provided support for replication of files (and incremental Hive partitions) between clusters, primarily to support disaster recovery scenarios.  Now customers can use Falcon to replicate Hive databases, tables and their underlying metadata -- complete with bootstrapping and reliably applying transactions to targets. 

Finally on the operations front, the pace of Apache Ambari innovations continues to astonish.  As part of HDP 2.3, Ambari arrives with support for significantly wider range of component deployment and monitoring support than ever before.  This includes the abilities to install and manage: Accumulo, DataFu, Mahout, and the Phoenix Query Server (Tech Preview) along with expanding its ability to configure the NFS Gateway capability of HDFS.  In addition, Ambari now provides support for rack awareness – allowing you to define and support the visualization of your data topology by rack.

We introduced the automation for rolling upgrade as part of Ambari 2.0, but this was primarily focused on automating the application of maintenance releases to your running cluster.  Now, Ambari expands its reach to support rolling upgrade for feature bearing releases as well.  Automating the ability for you to roll from HDP 2.2 to HDP 2.3.

Following the general availability of HDP 2.3, Cloudbreak will also become generally available.  Since the acquisition of SequenceIQ, the integrated team has been working hard to complete the deployment automation for public clouds like Microsoft Azure.

With Cloudbreak, operators will be able to seamlessly deploy elastic HDP clusters to Azure IaaS virtual machines. HDP will efficiently utilize Azure resources, with policy-based autoscaling to expand and contract clusters based upon actual usage metrics.

Operators will be able to deploy using a Cloudbreak web interface as well as a RESTful API.

Proactive Support with Hortonworks SmartSense™

In addition to all of the tremendous platform innovation, Hortonworks is proud to announce Hortonworks SmartSense which adds proactive cluster monitoring and delivers critical recommendations to customers who opt into this extended support capability.  The addition of Hortonworks SmartSense further enhances Hortonworks’ world-class support for Hadoop.

Hortonworks’ support subscription customers simply download the Hortonworks Support Tool (HST) from the support portal and deploy it to their cluster.  HST then collects configuration and other operational information about their HDP cluster and packages it up into a bundle.  After uploading this information bundle to the Hortonworks’ support team, we use our platform to analyze all the information it provides using more than 80 distinct checks performed across the underlying operating system, HDFS, YARN, MapReduce, Tez, and Hive components. 

Of course, there is so much more that I didn’t cover here which is also part of HDP 2.3!  There has been meaningful innovation within Hive for supporting Union within queries and using interval types in expressions, additional improvements for HBase, Phoenix, and more.  But, for now, I’ll leave those for subsequent blog posts that will highlight them all in more detail.

In closing, I would like to thank the entire Hortonworks team and the Apache community - including Microsoft developers - for the hard work put in over the past six to eight months.  That hard work is about to pay off in a big way for folks adopting Hadoop today as much as it will delight those who have been using Hadoop for years.

Thursday, June 4, 2015 10:00:00 AM

HP recently announced (see HP Announcement) the certification of the powerful scale-up Superdome X server. It is purposefully designed to support the most demanding, critical workloads for Windows Server and support for SQL Server as it is certified to run on Windows Server and provide support for SQL Server.

HP, in collaboration with Microsoft, is now releasing a new Reference Configuration for running Microsoft SQL Server in Superdome X.  A Reference Configuration is a specific solution designation that includes a solution Bill of Material (BOM), deployment steps and sizing testing to help users efficiently deploy SQL Server on Superdome X.  (Download the Reference Configuration guide: Here)

 

This solution will let customers scale-up their SQL Server environment to new heights.  The just released Reference Configuration guide provides specific configuration details for scaling up SQL Server 2014 supporting large scale online transaction processing (OLTP) workloads on the HP Integrity Superdome X.  Example configurations show scalability as 1, 2 and then 4 blades are used to size the SQL Server 2014 database workloads and provide comparison with previous server technology to highlight advancements made.

Microsoft SQL Server 2014 includes built-in in-memory capabilities optimized for each workload including OLTP, data warehousing, and business intelligence. The new in-memory OLTP engine can improve transaction throughput by up to 30x ,and significantly improve concurrency in parallel by running memory optimized tables and store procedures directly in-memory.  In addition, SQL Server 2014 offers an enhanced in-memory ColumnStore that offers up 100x faster queries with much higher data compression.  Whether you have a large number of concurrent, short-lived queries, or large and complex – Superdome X powerful architecture with up to 240 cores and 12 TB of RAM - will deliver the high performance and low latency required for decision support and business processing workloads.  Mission critical SQL Server 2014 solutions not only include large system scale-up, but also SQL Server consolidation projects (for multi-instance consolidation) and multi-partition consolidation solutions. The HP Integrity Superdome X solution has the flexibility to power all of these mission critical environments.

 

Mission Critical HP Integrity Superdome X with SQL Server

The Reference Configuration Guide covers the specific case for running SQL Server 2014 on the HP Superdome X platform for a large, scale-up, tier 1 OLTP workload.  The guide includes a detailed BOM necessary to best run these workloads with HP hardware and Microsoft software.  Here is an example of the scalability for SQL Server you can find detailed in the guide.

You can now download the Reference Configuration Guide at: Reference Configuration Superdome X-SQL Server

To gain more familiarity on running Windows Server and SQL Server on this new server platform, there is a new refreshed white paper to help: Running Microsoft Windows Server-SQL Server on Superdome X

Stay tuned as we are continuing our work with HP to develop and test the next level of solutions with more Reference Configuration and Reference Architecture becoming live in the next few months.

Tuesday, June 2, 2015 10:00:00 AM

Do you want to assess the health of your SQL Server deployments on Azure Virtual machines? 

Do you want to ensure that you have an optimal SQL Server configuration?

 

At Ignite 2015 we released a tool for this.  The Operations Management Suite (OMS) is a collection of IT management solutions powered by a modern cloud-based management platform that enables you to gain visibility on deployments across both cloud and on-premises.  It also helps you take control of your IT environment by remediating problems and orchestrating complex & repetitive operations through automation.

Included in OMS is the SQL Assessment which evaluates the configuration and assesses the health of your SQL Server deployments. It considers around 90 best practices defined by the SQL Server and Support Services teams. Based on these, it provides a prioritized list of recommendations tailored to your deployments.  

The recommendations are categorized across six Focus Areas. These areas allow you quickly understand the health of your deployments and easily take actions to enhance your SQL Server environments.

 

Are you ready to assess your SQL Server deployments in Azure Virtual Machine? 

To begin, setup your OMS workspace by following this step-by-step instructions.

Once the workspace is established, add the SQL Assessment to your workspace.  To start collecting configuration and telemetry data install the OMS Agent or the Systems Center Operations Manager Agent.

Data collection will start after the agents are installed. Keep in mind that the first assessment will be available a couple of hours later,  after the data is gathered and analyzed. At that point, you will see the data populated in the SQL Assessment tile.

 

Learn more about OMS here and try the Operations Management Suite today for free!

 

Wednesday, May 27, 2015 11:00:00 AM

Three weeks ago at Microsoft Ignite, we announced SQL Server 2016, the next major release of Microsoft’s flagship database and analytics platform, as well key innovations in the release.  Today we are pleased to announce the first public Community Technology Preview (CTP2) for SQL Server 2016.  This public preview gives an early look into many of the capabilities in the release and allows early adopters to get engaged by testing the preview in their environments or via a virtual machine in Microsoft Azure. 

SQL Server 2016 provides breakthrough performance for mission critical applications and deeper insights on your data across on-premises and cloud. Top capabilities for the release include: Always Encrypted - a new capability that protects data at rest and in motion, Stretch Database - new technology that lets you dynamically stretch your warm and cold transactional data to Microsoft Azure, enhancements to our industry-leading in-memory technologies for real-time analytics on top of breakthrough transactional performance and new in-database analytics with R integration. 

Unique in this release of SQL Server, we are bringing capabilities to the cloud first in Microsoft Azure SQL Database such as Row-level security and Dynamic Data Masking and then bringing the capabilities, as well as the learnings from running these at hyper-scale in Microsoft Azure, back to SQL Server to deliver proven features at scale to our on-premises offering.  This means all our customers benefit from our investments and learnings in Azure. 

Key Capabilities in SQL Server 2016 CTP2

Always Encrypted

Always Encrypted, based on technology from Microsoft Research, protects data at rest and in motion. With Always Encrypted, SQL Server can perform operations on encrypted data and best of all, the encryption key resides with the application in the customers trusted environment. Encryption and decryption of data happens transparently inside the application which minimizes the changes that have to be made to existing applications.

Stretch Database

This new technology allows you to dynamically stretch your warm and cold transactional data to Microsoft Azure, so your operational data is always at hand, no matter the size, and you benefit from the low cost of Azure.  You can use Always Encrypted with Stretch Database to extend data in a more secure manner for greater peace of mind.

Real-time Operational Analytics & In-Memory OLTP

For In-Memory OLTP, which customers today are using for up to 30x faster transactions, you will now be able to apply this tuned transaction performance technology to a significantly greater number of applications and benefit from increased concurrency.  With these enhancements, we introduce the unique capability to use our in-memory columnstore delivering 100X faster queries on top of in-memory OLTP to provide real-time operational analytics while accelerating transaction performance.

Additional capabilities in SQL Server 2016 CTP2 include:

  • PolyBase – More easily manage relational and non-relational data with the simplicity of T-SQL.
  • AlwaysOn Enhancements – Achieve even higher availability and performance of your secondaries, with up to 3 synchronous replicas, DTC support and round-robin load balancing of the secondaries.
  • Row Level Security– Enables customers to control access to data based on the characteristics of the user. Security is implemented inside the database, requiring no modifications to the application.
  • Dynamic Data Masking – Supports real-time obfuscation of data so data requesters do not get access to unauthorized data.  Helps protect sensitive data even when it is not encrypted.
  • Native JSON support – Allows easy parsing and storing of JSON and exporting relational data to JSON.
  • Temporal Database support – Tracks historical data changes with temporal database support.
  • Query Data Store – Acts as a flight data recorder for a database, giving full history of query execution so DBAs can pinpoint expensive/regressed queries and tune query performance.
  • MDS enhancements – Offer enhanced server management capabilities for Master Data Services.
  • Enhanced hybrid backup to Azure – Enables faster backups to Microsoft Azure and faster restores to SQL Server in Azure Virtual Machines.  Also, you can stage backups on-premises prior to uploading to Azure.

Ongoing preview updates – Coming soon!

New with SQL Server 2016, customers will have the opportunity to receive more frequent updates to their preview to help accelerate internal development and test efforts.  Instead of waiting for CTP3, customers can choose to download periodic updates to CTP2 gaining access to new capabilities and features as soon as they are available for testing.  More details will be shared when the first preview update is available. 

Download SQL Server 2016 preview today!

Now that you have seen the many exciting capabilities included in SQL Server 2016 CTP2, be sure to download the preview or trial the preview using a virtual machine in Microsoft Azure and start evaluating the impact these new innovations can have for your business.  Also, be sure to share your feedback on the new SQL Server 2016 capabilities using Microsoft’s Connect tool

As the foundation of our end-to-end data platform, with this release we continue to make it easier for customers to maximize their data dividends. With SQL Server 2016 you can capture, transform, and analyze any data, of any size, at any scale, in its native format —using the tools, languages and frameworks you know and want in a trusted environment on-premises and in the cloud.

To learn more about the release, visit the SQL Server 2016 preview page.  We look forward to hearing from you!

Tuesday, May 19, 2015 11:00:00 AM

Brian Mitchell, Microsoft Senior Business Program Manager, took the stage at Ignite two weeks ago to discuss Planning Your Big Data Architecture on Azure. “Big Data” requires big scale. Mitchell covered how this is accomplished through storage strategies, partitioning, fault tolerance, and the right architecture to scale to the extremes of big data. If you want to explore cloud-based big data apps, be sure to check it out.

Ignite covered the cloud in depth. Make sure to take a look at all the other on-demand presentations, demos, and more.

Friday, May 15, 2015 2:30:00 PM

Today, we are pleased to announce the availability of SQL Server 2014 Service Pack 1 (SP1). The Service Pack is available for download on the Microsoft Download Center. This upgrade is available to all customers with existing SQL Server 2014 deployments.

For more highlights of the release, please read the Knowledge Base Article for Microsoft SQL Server 2014 SP1. To obtain SQL Server 2014 SP1 with its improved supportability, please visit the links below.

 

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