Microsoft has officially announced the release of SQL Server 2016 as June 1, 2016
SQL 2016 has a number of major
enhancements which will help whether or not you are implementing on-prem, in
Azure or in a hybrid model.
Top 7 Features Coming to SQL
Server 2016
Query Store
One common problem many organizations face when upgrading versions of SQL Server is changes in the query optimizer (which happen from version to version) negatively impacting performance. Without comprehensive testing, this has traditionally been a hard problem to identify and then resolve. The Query Store feature maintains a history of query execution plans with their performance data, and quickly identifies queries that have gotten slower recently, allowing administrators or developers to force the use of an older, better plan if needed. The Query Store is configured at the individual database level.
One common problem many organizations face when upgrading versions of SQL Server is changes in the query optimizer (which happen from version to version) negatively impacting performance. Without comprehensive testing, this has traditionally been a hard problem to identify and then resolve. The Query Store feature maintains a history of query execution plans with their performance data, and quickly identifies queries that have gotten slower recently, allowing administrators or developers to force the use of an older, better plan if needed. The Query Store is configured at the individual database level.
Polybase
Microsoft had introduced
Polybase, a SQL Server connector to Hadoop (and Azure Blob Storage) to its data
warehouse appliance Analytics Platform System in 2015. But now Microsoft has
incorporated that functionality into the regular on-premises product. This
feature will benefit you if your regular data processing involves dealing with
a lot of large text files.they can be stored in Azure Blob Storage or Hadoop,
and queried as if they were database tables. A common scenario where you might
use this would be an extract, transform and load (ETL) process, where you were
taking a subset of the text file to load into your database.
Stretch Database
If you are buying enterprise-class SAN storage or enterprise SSDs, you will know that storage is still very expensive. Microsoft is trying to help reduce your storage (and processing costs) with a hybrid feature called "Stretch Database." The basics of Stretch Database are that some part of your tables (configurable or automated) will be moved into an Azure SQL Database in the cloud in a secure fashion. When you query those tables, the query optimizer knows which rows are on your server and which rows are in Azure, and divides the workload accordingly. The query processing on the Azure rows takes place in Azure so the only latency is for the return of the rows over the network. As an additional enhancement, you are only charged for the SQL Database in Azure when it is used for queries. You do, however, pay for the Azure Blob storage, which, generally speaking, is much cheaper than enterprise storage.
If you are buying enterprise-class SAN storage or enterprise SSDs, you will know that storage is still very expensive. Microsoft is trying to help reduce your storage (and processing costs) with a hybrid feature called "Stretch Database." The basics of Stretch Database are that some part of your tables (configurable or automated) will be moved into an Azure SQL Database in the cloud in a secure fashion. When you query those tables, the query optimizer knows which rows are on your server and which rows are in Azure, and divides the workload accordingly. The query processing on the Azure rows takes place in Azure so the only latency is for the return of the rows over the network. As an additional enhancement, you are only charged for the SQL Database in Azure when it is used for queries. You do, however, pay for the Azure Blob storage, which, generally speaking, is much cheaper than enterprise storage.
JSON support
In addition to supporting direct
querying to Hadoop, SQL Server 2016 adds support for the lingua franca of Web
applications: Java Script Object Notation (JSON). Several other large databases
have added this support in recent years as the trend towards Web APIs using
JSON has increased. The way this is implemented in SQL 2016 is very similar to
the way XML support is built in with FOR JSON and OPENJSON -- providing the
ability to quickly move JSON data into tables.
Always
Encrypted
we hear about some company having a major data breach. Encryption works, but many companies do not or cannot implement it all the way through the stack, leaving some layer data available for the taking as plain text. SQL Server has long supported both column-level encryption, encryption at rest, and encryption in transit. However these all had to be configured independently and were frequently misconfigured. Always Encrypted is new functionality through the use of an enhanced client library at the application so the data stays encrypted in transit, at rest and while it is alive in the database. Also given Microsoft's push towards the use of Azure, easy encryption makes for a much better security story.
we hear about some company having a major data breach. Encryption works, but many companies do not or cannot implement it all the way through the stack, leaving some layer data available for the taking as plain text. SQL Server has long supported both column-level encryption, encryption at rest, and encryption in transit. However these all had to be configured independently and were frequently misconfigured. Always Encrypted is new functionality through the use of an enhanced client library at the application so the data stays encrypted in transit, at rest and while it is alive in the database. Also given Microsoft's push towards the use of Azure, easy encryption makes for a much better security story.
In-Memory
Enhancements
SQL Server 2014 introduced the concept of in-memory tables. These were optimally designed for high-speed loading of data with no locking issues or high-volume session state issues. While this feature sounded great on paper, there were a lot of limitations particularly around constraints and procedures. In SQL Server 2016, this feature is vastly improved, supporting foreign keys, check and unique constraints and parallelism. Additionally, tables up to 2TB are now supported (up from 256GB). Another part of in-memory is column store indexes, which are commonly used in data warehouse workloads. This feature was introduced in SQL 2012 and has been enhanced in each version since. In 2016 it receives some enhancements around sorting and better support with AlwaysOn Availability Groups.
SQL Server 2014 introduced the concept of in-memory tables. These were optimally designed for high-speed loading of data with no locking issues or high-volume session state issues. While this feature sounded great on paper, there were a lot of limitations particularly around constraints and procedures. In SQL Server 2016, this feature is vastly improved, supporting foreign keys, check and unique constraints and parallelism. Additionally, tables up to 2TB are now supported (up from 256GB). Another part of in-memory is column store indexes, which are commonly used in data warehouse workloads. This feature was introduced in SQL 2012 and has been enhanced in each version since. In 2016 it receives some enhancements around sorting and better support with AlwaysOn Availability Groups.
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