The Features that previously were only available to customers willing to part with in excess of £25,000 for an Enterprise licence can now take advantage of the following features absolutely free and in ALL editions of SQL Server 2016 with SP1.
Database Snapshots
A database snapshot is a read-only, static view of a SQL Server database.
Change Data Capture
Change data capture records insert, update, and delete activity that is applied to a SQL Server table. This makes the details of the changes available in an easily consumed relational format.
Column Store Indexes
The columnstore index is the standard for storing and querying large data warehousing fact tables. It uses column-based data storage and query processing to achieve up to 10x query performance gains in your data warehouse over traditional row-oriented storage, and up to 10x data compression over the uncompressed data size.
In Memory OLTP
In-Memory OLTP can significantly improve the performance of transaction processing, data ingestion and data load, and transient data scenarios.
Table and Index Partitioning
SQL Server supports table and index partitioning. The data of partitioned tables and indexes is divided into units that can be spread across more than one filegroup in a database. The data is partitioned horizontally, so that groups of rows are mapped into individual partitions.
Data Compression
SQL Server 2016 supports row and page compression for row store tables and indexes, and supports columnstore and columnstore archival compression for columnstore tables and indexes.
Multiple FileStream Containers
FILESTREAM enables SQL Server-based applications to store unstructured data, such as documents and images, on the file system. Applications can leverage the rich streaming APIs and performance of the file system and at the same time maintain transactional consistency between the unstructured data and corresponding structured data.
Always Encrypted Data
Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national Security numbers , stored in SQL Server databases. Always Encrypted allows clients to encrypt sensitive data inside client applications and never reveal the encryption keys to the Database Engine. As a result, Always Encrypted provides a separation between those who own the data (and can view it) and those who manage the data (but should have no access).
Dynamic Data Masking
Dynamic data masking limits (DDM) sensitive data exposure by masking it to non-privileged users. It can be used to greatly simplify the design and coding of security in your application.
Dynamic data masking helps prevent unauthorized access to sensitive data by enabling customers to designate how much of the sensitive data to reveal with minimal impact on the application layer. DDM can be configured on the database to hide sensitive data in the result sets of queries over designated database fields, while the data in the database is not changed. Dynamic data masking is easy to use with existing applications, since masking rules are applied in the query results. Many applications can mask sensitive data without modifying existing queries
Row Level Security
Row-Level Security enables customers to control access to rows in a database table based on the characteristics of the user executing a query (e.g., group membership or execution context).
Row-Level Security (RLS) simplifies the design and coding of security in your application. RLS enables you to implement restrictions on data row access. For example ensuring that workers can access only those data rows that are pertinent to their department, or restricting a customer's data access to only the data relevant to their company.
PolyBase Compute Node
PolyBase is a technology that accesses and combines both non-relational and relational data, all from within SQL Server. It allows you to run queries on external data in Hadoop or Azure blob storage. The queries are optimized to push computation to Hadoop
By simply using Transact-SQL (T-SQL) statements, you an import and export data back and forth between relational tables in SQL Server and non-relational data stored in Hadoop or Azure Blob Storage. You can also query the external data from within a T-SQL query and join it with relational data.
