New In-Memory OLTP Engine
Most important feature introduced in SQL Server 2014 is the In-Memory 
OLTP engine  By moving select tables and 
stored procedures into memory, you can drastically reduce I/O and 
improve performance of your OLTP applications.
The
 In-Memory OLTP engine is designed for high concurrency and uses a new 
optimistic concurrency control mechanism to eliminate locking delays. 
The In-Memory OLTP tables are copied into memory and made durable by 
transaction log writes to disk. An all-new lock-free engine processes 
the transactions for memory-resident tables. Stored procedure 
performance is improved by compiling the stored procedures into native 
code DLLs. Standard T-SQL stored procedures are interpreted, which adds 
overhead to the execution process. Compiling the stored procedures to 
native Win64 code makes them directly executable, thereby maximizing 
their performance and minimizing execution time.
                               Enhancements to AlwaysOn Availability Groups
SQL
 Server 2014's AlwaysOn Availability Groups has been enhanced with 
support for additional secondary replicas and Windows Azure integration.
 First introduced with SQL Server 2012, AlwaysOn Availability Groups 
boosted SQL Server availability by providing the ability to protect 
multiple databases with up to four secondary replicas. In SQL Server 
2014, Microsoft has enhanced AlwaysOn integration by expanding the 
maximum number of secondary replicas from four to eight. Readable 
secondary replicas are now available for read-only workloads, even when 
the primary replica is unavailable. SQL Server 2014 also provides 
Windows Azure AlwaysOn integration. This new integration feature enables
 you to create asynchronous availability group replicas in Windows Azure
 for disaster recovery. In the event of a local database outage, you can
 run your SQL Server databases from Windows Azure VMs. The new Windows 
Azure AlwaysOn availability options are fully integrated into SQL Server
 Management Studio (SSMS).
                               Enhancements to Backups
Database
 backups in SQL Server now support built-in database encryption. 
Previous releases all required a third-party product to encrypt database
 backups. The backup encryption process uses either a certificate or an 
asymmetric key to encrypt the data. The supported backup encryption 
algorithms are Advanced Encryption Standard (AES) 128, AES 192, AES 256,
 and Triple DES (3DES).
                               Updateable Columnstore Indexes
Columnstore
 indexes are another of Microsoft's high performance in-memory 
technologies. Microsoft introduced the columnstore index in SQL Server 
2012 to provide significantly improved performance for data warehousing 
types of queries. Microsoft states that for some types of queries, 
columnstore indexes can provide up to 10x performance improvements. 
However, in the original implementation of the columnstore indexes, the 
underlying table had to be read-only. SQL Server 2014 eliminates this 
restriction. The new updateable columnstore index enables updates to be 
performed to the underlying table without first needing to drop the 
columnstore index. A SQL Server 2014 columnstore index must use all of 
the columns in the table, and it can't be combined with other indexes.
Buffer Pool Extension
SQL 
Server 2014 provides a new solid state disk (SSD) integration capability
 that lets you use SSDs to expand the SQL Server 2014 Buffer Pool as 
nonvolatile RAM (NvRAM). With the new Buffer Pool Extensions feature, 
you can use SSD drives to expand the buffer pool in systems that have 
maxed out their memory. Buffer Pool Extensions can provide performance 
gains for read-heavy OLTP workloads.
Power View for Multidimensional Models
Power
 View used to be limited to tabular data. However, with SQL Server 2014,
 Power View can now be used with multidimensional models (OLAP cubes) 
and can create a variety of data visualizations including tables, 
matrices, bubble charts, and geographical maps. Power View 
multidimensional models also support queries using Data Analysis 
Expressions (DAX).
 
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