What’s New in SQL Server 2019 since SQL Server 2017
What’s New in SQL Server 2017 since SQL Server 2016
Database Engine
Enhancements on Windows
Enhancements in the
SQL Server 2019 database engine are not limited to PolyBase and Big Data
Clusters; many components of the database engine have new features and
capabilities with this release. The following features are added or enhanced
for SQL Server 2019 CTP 2.0.
- UTF-8
support
- Resumable
online index create allows index create to resume after interruption
- Clustered
columnstore online index build and rebuild
- Always
Encrypted with secure enclaves
- Intelligent
query processing
- Java
language programmability extension
- SQL
Graph features
- Database
scoped configuration setting for online and resumable DDL operations
- Enhancement
in Always On Availability Groups
- Data
discovery and classification - natively built into SQL Server
- Expanded
support for persistent memory devices
- Support
for columnstore statistics in DBCC CLONEDATABASE
- New
options added to sp_estimate_data_compression_savings
- SQL
Server Machine Learning Services failover clusters
- Lightweight
query profiling infrastructure enabled by default
- New
PolyBase connectors
- New
sys.dm_db_page_info system function returns page information
Let's look at some of the added
features that I believe will be the most useful to users of the database
management system (DBMS).
AlwaysOn Availability Groups
SQL Server 2019 adds support for even
more high availability scenarios and platforms, including:
Enable high availability configurations
for SQL Server running in containers - SQL Server 2019 enables customers to
configure highly-available systems with AlwaysOn Availability Groups using
Kubernetes as an orchestration layer.
Up to five synchronous replica pairs –
SQL Server 2019 increases the limit for synchronous replica pairs from three
(in SQL Server 2017) to five. Users can now configure up to five synchronous
replicas (1 Primary and up to 4 secondary replicas) with automatic failover
between these replicas.
Better scale-out with automatic
redirection of connections based on read/write intent - Configuring an AlwaysOn
Availability can be challenging for a number of reasons, including:
- In
SQL Server 2017, an administrator must configure the Availability Group
listener (and the corresponding cluster resource) to direct SQL Server
traffic to the primary replica to ensure that clients are transparently
reconnected to the active primary node upon failover; however, there are
cluster technologies that support SQL Server Availability Groups that do
not offer a listener-like capability.
- In
a multi-subnet configuration such as Azure or multi-subnet floating IP
address in an availability group using Pacemaker, configurations become
complex, prone to errors and difficult to troubleshoot due to multiple
components involved.
- When
the availability group is configured for read scale-out or DR and cluster
type is NONE, there is no straightforward mechanism to ensure transparent
reconnection upon manual failover.
To address these challenges, SQL Server
2019 adds a new feature for Availability Groups: secondary to primary replica
connection redirection. With this feature, client applications can connect to
any of the replicas of the Availability Group and the connection will be
redirected to the primary replica, according to the Availability Group
configuration and the connection intent (read only or read/write) specified in
the connection string
Data discovery and classification
SQL Data Discovery and Classification
allows to classify columns in the database that contain sensitive information.
Columns can be classified by the type of information it contains. For example
names, addresses, social security numbers etc and by the level of sensitive
data in the column including levels such as public, general and confidential.
We can easily generate reports from the classification that are applied to meet
statutory and regulatory requirements, such as EU GDPR. SSMS also includes the
SQL Data Discovery and Classification wizard, which will try to identify
columns in the database that contain sensitive information. SQL Data Discovery
and Classification uses the underlying mechanism of SQL Server Extended
Properties, and so is backwards-compatible with SQL Server 2008 and later
Always Encrypted with Secure Enclaves
Introduced in SQL Server 2016, Always
Encrypted is an encryption technology that protects the confidentiality of
sensitive data from malware and high-privileged, but unauthorized users of SQL
Server, including DBAs, machine admins and cloud admins. Sensitive data is
never visible in plain-text to those users.
The secure enclave technology, introduced
in SQL Server 2019, addresses the limitations of Always Encrypted by allowing
computations on plain-text data within a secure enclave inside the SQL Server
process. A secure enclave is a protected region of memory within the SQL Server
process, and it acts as a trusted execution environment for processing
sensitive data inside the SQL Server Engine. A secure enclave extends client
applications’ trust boundary to the server side. While it is contained by the
SQL Server environment, the secure enclave is not accessible to SQL Server, the
operating system, or to the database or system administrators.
Clustered columnstore online index
build and rebuild
Creating clustered columnstore indexes
(CCI) was an offline process in the previous versions of SQL Server - requiring
all changes stop while the CCI is created.
With SQL Server 2019 preview and Azure
SQL Database we can create or re-create clustered columnstore index online.
Workload will not be blocked and all changes made on the underlying data are
transparently added into the target columnstore table.
Expanded support for persistent memory
devices
Microsoft is improving persistent
memory support for this release. It’s doing so with a newly optimized I/O path
that’s meant to interact with persistent memory storage. When an SQL Server
file is placed on a persistent memory device, it allows SQL Server to access
the device directly, bypassing the operating system’s storage stack entirely.
Basically, this improves performance and low latency I/O without actually
changing your database design.
Intelligent query processing
The new Intelligent Query Processing
suite is meant to rectify some of the common query performance problems by
taking some automatic corrective approaches during run-time. It leverages a
feedback loop based on statistics collected from past executions. Microsoft has
already started leveraging some of these features in Azure SQL Database and
plans to continue building on this area for SQL Server 2019.
UTF-8 Support
SQL Server 2019 includes full support
for the widely used UTF-8 character encoding as an import or export encoding,
or as database-level or column-level collation for text data.
UTF-8 is allowed in the CHAR and
VARCHAR datatypes, and is enabled when creating or changing an object’s
collation,to a collation with the "UTF8" suffix,such as
LATIN1_GENERAL_100_CI_AS_SC to LATIN1_GENERAL_100_CI_AS_SC_UTF8. UTF-8 is only
available to windows collations that support supplementary characters, as
introduced in SQL Server 2012. Note that NCHAR and NVARCHAR allow UTF-16
encoding only, and remain unchanged.
Significant storage savings can also be
achieved, depending on the character set in use. For example, changing an existing
column data type from NCHAR(10) using UTF-16 to CHAR(10) using an UTF-8 enabled
collation, translates into nearly 50% reduction in storage requirements. This
is because NCHAR(10) requires 22 bytes for storage, whereas CHAR(10) requires
12 bytes for the same Unicode string.
Database Engine Enhancements on Linux
The following features are added or
enhanced for SQL Server 2019 preview CTP 2.
SQL Server on Linux
- Replication
support
- Support
for the Microsoft Distributed Transaction Coordinator (MSDTC)
- Always
On Availability Group on Docker containers with Kubernetes
- OpenLDAP
support for third-party AD providers
- Machine
Learning on Linux
- New
container registry
- New
RHEL-based container images
- Memory
pressure notification
Replication support
SQL Server 2019 preview supports SQL
Server Replication on Linux. A Linux virtual machine with SQL Agent can be a
publisher, distributor, or subscriber. Create the following types of
publications
- Transactional
- Snapshot
- Merge
Configure replication SQL Server
Management Studio or use replication stored procedures
Support for the Microsoft Distributed
Transaction Coordinator (MSDTC)
SQL Server 2019 on Linux supports the
Microsoft Distributed Transaction Coordinator (MSDTC). SQL Server on Linux
instances can now initiate and participate in distributed transactions. This is
achieved with a Linux version of the Microsoft Distributed Transaction
Coordinator (MSDTC) that runs within the SQL Server process to help SQL Server
participate in distributed transactions. With access to MSDTC, SQL Server on
Linux can participate in distributed transactions with other third-party
transaction coordinators, or if you have specific processing needs there is
support for you to develop your own.
Active Directory Integration
Integration between SQL Server on Linux
and Active Directory is much improved. SQL Server on Linux instances can be
configured use Active Directory for authentication of users, for replication,
and for distributed queries. SQL Server on Linux instances can now participate
in Availability Groups that are authenticated by Active Directory, in addition
to the support for certificate-based authentication included in SQL Server 2017
on Linux. As an alternative to Active Directory, SQL Server on Linux instances
can now use OpenLDAP as a directory provider, making it easier to manage
domain-joined Linux servers.
Always On Availability Group on Docker
containers with Kubernetes
Kubernetes can orchestrate containers
running SQL Server instances to provide a highly available set of databases
with SQL Server AlwaysOn Availability Groups. A Kubernetes operator deploys a
StatefulSet including a container with mssql-server container and a health
monitor.
OpenLDAP support for third-party AD
providers
SQL Server 2019 preview on Linux
supports OpenLDAP, which allows third-party providers to join Active Directory.
Machine Learning on Linux
There are many advantages to bringing
the machine learning compute to the data instead of moving data out to compute.
These advantages include the elimination of data movement, ease of deployment,
improved security and better scale and performance. These advantages also make
SQL Server a powerful end to end machine learning platform. Enhancements to
Machine Learning in SQL Server 2019 CTP 2.0 include:
- Machine
Learning on Linux: SQL Server 2019 Machine
Learning Services (In-Database) is now supported on Linux.
- Input
data partitioning: without changing your R or
Python scripts, you can process data at table partition level. This allows
you to train a model for each table partition and parallelize model
training per partition.
- Failover
cluster support: You can install SQL Server
2019 Machine Learning Services (In-Database) on a Windows failover cluster
to meet your requirements for redundancy and uptime in the event your
primary server fails over.
- Java
language extension: In addition to R and Python
runtimes, SQL Server 2019 adds a Java language extension. This will allow
you to call a pre-compiled Java program and securely execute Java code on
SQL Server. This reduces the need to move data and improves application
performance by bringing your workloads closer to your data. You specify
the Java runtime you want to use, by installing the JDK distribution and
Java version of your choice.
Container
All container images for SQL Server
2019 preview as well as SQL Server 2017 (14.x) are now located in the Microsoft
Container Registry. Microsoft Container Registry is the official container
registry for the distribution of Microsoft product containers. In addition,
certified RHEL-based images are now published.
- Microsoft
Container Registry: mcr.microsoft.com/mssql/server:vNext-CTP2.0
- Certified
RHEL-based container images: mcr.microsoft.com/mssql/rhel/server:vNext-CTP2.0
What’s New in SQL Server 2017 since SQL Server 2016
The changes introduced in SQL Server 2017 discussed here
include the following features:
SQL Server
on Linux
SQL Server is no longer just a windows-based relational
database management system (RDBMS). You can run it on different flavors of the
Linux operating systems. You can also develop applications with SQL Server on Linux,
Windows, Ubuntu operating systems, or Docker and deploy them on these
platforms.
Resumable online index rebuild
This feature resumes an online index rebuild operation
from where it stopped after events such as database failovers, running out of
disk space, or pauses.
GUIDELINES FOR INDEXING
When you perform online index operations, the following
guidelines apply:
·
Clustered indexes must be created,
rebuilt, or dropped offline when the underlying table contains image, ntext,
and text large object (LOB) data types.
·
Non-unique and non-clustered indexes
can be created online when the table contains LOB data types but none of these
columns are used in the index definition as either key or as non-key (included)
columns.
·
Indexes on local temporary tables
cannot be created, rebuilt, or dropped online. This restriction does not apply
to indexes on global temporary tables.
·
You can perform concurrent online
index data definition language (DDL) operations on the same table or view only
when you are creating multiple new non-clustered indices, or reorganizing
non-clustered indices. All other online index operations performed at the same
time fail. For example, you cannot create a new index online while rebuilding
an existing index online on the same table.
SQL Server machine learning services
SQL Server 2016 integrated the R programming language,
which can be run within the database server and can be embedded into a
Transact-SQL (T-SQL) script, too. In SQL Server 2017, you can execute the
Python script within the database server itself. Both R and Python are popular
programming languages that provide extensive support for data analytics along
with natural language processing capability.
Query processing improvements
SQL Server 2017 adapts optimization strategies to your
application workload’s runtime conditions. It includes adaptive query
processing features that you can use to improve query performance in SQL Server
and SQL Database.
·
Batch mode
memory grant feedback: This feedback technique
recalculates required memory for the execution plan and grants it from cache.
·
Batch mode
adaptive joins: To execute the plan faster, this technique
can use a hash join or a nested loop join. After scanning the first input of
the execution plan, it decides which join to use to produce output at the
fastest speed.
·
Interleaved
execution: Interleaved execution pauses
optimization of an execution plan when it encounters multi-statement
table-valued functions. Then, it calculates perfect cardinality and resumes
optimization.
Automatic database tuning
This feature notifies you whenever a potential performance
issue is detected and enables you to apply corrective actions, or it enables
the database engine to automatically fix performance issues caused by the SQL
plan choice regressions. Thus, the database can dynamically adapt to your
workload by finding what indexes and plans might improve performance of your
workloads and what indexes affect your workloads. Based on these findings, the
automatic tuning process applies actions that improve the workload performance.
In addition, the database continuously monitors performance after any change
made by automatic tuning to ensure that it improves the workload performance.
Any action that doesn’t improve performance is automatically reverted.
SQL PLAN CHOICE REGRESSION
The SQL Server database engine may use different SQL plans
to execute the T-SQL queries. Query plans depend on the statistics, indexes,
and other factors. In some cases, the new plan might not be better than the
previous one, and the new plan might cause a performance regression. Whenever
you notice a poor plan choice regression, you should find a previously used
good plan and force it to be used instead of the current one by using the sp_query_store_force_plan procedure. The database engine in SQL Server 2017
(v. 14.x) provides information about regression plans and recommended
corrective actions. Additionally, the database engine enables you to fully
automate this process and let the database engine fix any problems related to
the plan changes that are found.
AUTOMATIC PLAN CORRECTION
·
Automatic
plan correction (available in SQL Server 2017
v14.x and Azure SQL Database): It identifies problematic query execution plans
and fixes the SQL plan performance problems
·
Automatic
index management (available only in Azure SQL
Database): It identifies indexes that should be added in your database and
indexes that should be removed.
TempDB file size improvements
SQL Server 2017 setup now enables you to specify the
initial TempDB file size up to 256 GB (262,144 MB) per file, with a warning if
the file size is set greater than 1GB without instant file initialization
(IFI) enabled. It is important to understand that, depending
on the initial size of TempDB data file specified, not enabling IFI can cause
setup time to increase exponentially.
Smart differential backup
A
new column modified_extent_page_count is introduced in sys.dm_db_file_space_usage to track differential changes in each database file
in the database. The new column modified_extent_page_count allows DBAs, the SQL community, and backup
independent software vendors (ISVs) to build smart backup solutions, which perform
differential backups if the percentage of changed pages in the database is
below a threshold (approximately 70-80%). Otherwise, they perform a full
database backup. With a large number of changes in the database, the cost and
time to complete differential backups is similar to taking a full database
backup, so there is no real benefit of taking differential backup in this case.
However, it can certainly increase the restore time of database. By adding this
intelligence to the backup solutions, you can now save on restore and recovery
time by using differential backups.
Smart transaction log backup
A new Dynamic Management Function (DMF), sys.dm_db_log_stats (database_id), was released. This function exposes a new column, log_since_last_log_backup_mb, which empowers DBAs, the SQL community, and backup ISVs
to build intelligent T-log backup solutions to take backups based on the
transactional activity on the database. This T-log backup solution intelligence
ensures that, if the T-log backup frequency is too low, the transaction log
size doesn't grow due to a high burst of transactional activity in a short
time. It also helps to avoid a situation where the scheduled transaction log
backup creates too many T-log backup files even when there is no transactional
activity on the server. If that happened, it would add unnecessarily to the
storage, file management, and restore overheads.
Improved SELECT INTO statement
In SQL Server 2017, you can provide the filegroup name on
which to create a new table by using the ON keyword
with the SELECT INTO statement. The table is created on the default
filegroup of the user by default. This functionality was not available in
previous versions.
Distributed transaction support
SQL Server 2017 supports distributed transactions for
databases in availability groups. This support includes databases on the same
instance of SQL Server and databases on different instances of SQL Server.
Distributed transactions are not supported for databases configured for
database mirroring.
New availability groups functionality
This functionality includes clusterless support, the Minimum Replica Commit Availability Groups setting, and Windows-Linux cross-OS migrations and
testing.
This functionality includes the following features:
·
Availability groups can now be set up
without an underlying cluster (Windows Server Failover Cluster or WSFC) and
across mixed environments (instances on Windows and Linux or Docker).
·
The new Minimum Replica Commit setting enables you to dictate a certain number of
secondary replicas. You must commit a transaction before committing on the
primary.
New dynamic management views
The dynamic management views (DMVs) include the following
elements:
·
sys.dm_db_log_stats exposes
summary level attributes and information on transaction log files and is
helpful for monitoring transaction log health.
·
sys.dm_tran_version_store_space_usage enables
you to see the impact on version store usage, grouped by each database. As a
result, you can use this to profile your workload in a test environment (before
and after the change) and to monitor the impact over time–even if other
databases are also using version store.
·
sys.dm_db_log_info exposes
virtual log file (VLF) information to monitor, alert, and avert potential
transaction log issues.
·
sys.dm_d_stats_histogram is
a new dynamic management view for examining statistics.
·
sys.dm_os_host_info exposes
things like platform, distribution, service pack level, and language.
·
sys.dm_os_sys_info was
expanded, revealing CPU information (such as socket count, core count, and
cores per socket).
In-memory enhancements
The in-memory changes in SQL Server 2017 include the
following enhancements:
·
Computed column, and indexes on those
columns, are now supported.
·
CASE expressions, CROSS APPLY, and
TOP (N) WITH TIES are now supported in natively-compiled modules.
·
JSON commands are now fully supported
in both check constraints and in natively-compiled modules.
·
The system procedure sp_spaceused now
properly reports space for memory-optimized tables.
·
The system procedure sp_rename now
works on in-memory tables and natively-compiled modules.
·
The limitation of eight indexes on
memory-optimized tables has been eliminated.
·
Memory-optimized filegroup files can
now be stored on Azure storage.
Security enhancement
You can now grant, deny, or revoke permissions on
database-scoped credentials such as CONTROL, ALTER, REFERENCES, TAKE OWNERSHIP,
and VIEW DEFINITION permissions. Also, ADMINISTER DATABASE BULK OPERATIONS is
now visible in sys.fn_builtin_permissions.
High availability and disaster recovery
Gain mission-critical uptime, fast failover, easy setup,
and load balancing of readable secondaries with enhanced Always On functionality in SQL Server 2017. This is a unified
solution for high availability and disaster recovery on Linux and Windows. You
can also put an asynchronous replica in an Azure virtual machine for hybrid
high availability.
Performance improvements
SQL Server 2017 introduces the following changes to the
way queries and statistics are collected and displayed:
·
A new DMV sys.dm_exec_query_statistics_xml allows
you to correlate sessions to plans, as long as query profiling is enabled.
·
Showplan XML now includes information
about the statistics used for a plan and, for actual plans, runtime metrics and
the top 10 wait statistics experienced by that plan. These wait statistics are
also now being tracked in the query store.
·
A new dynamic management
function sys.dm_db_stats_histogram enables
you to access histogram information programmatically, without databases console
commands (DBCC).
What’s New in SQL Server 2016 since SQL Server 2014
Always
Encrypted
With
the Always Encrypted feature enabled your SQL Server data will always be
encrypted within SQL Server. Access to encrypted data will only be available to
the applications calling SQL Server. Always Encrypted enables client
application owners to control who gets access to see their applications
confidential data. It does this by allowing the client application to be
the one that has the encryption key. That encryption key is never passed
to SQL Server. By doing this you can keep those nosey Database or Windows
Administrators from poking around sensitive client application data In-Flight
or At-Rest. This feature will now allow you to sleep at night knowing your
confidential data stored in a cloud managed database is always encrypted and
out of the eyes of your cloud provider.
Dynamic
Data Masking
If
you are interested in securing your confidential data so some people can see
it, while other people get an obscured version of confidential data then you
might be interested in dynamic data masking. With dynamic data masking
you can obscure confidential columns of data in a table to SQL Server for users
that are not authorized to see the all the data. With dynamic data
masking you can identify how the data will be obscured. For instance say
you accept credit card numbers and store them in a table, but you want to make
sure your help desk staff is only able to see the last four digits of the
credit card number. By setting up dynamic data masking you can define a masking
rules so unauthorized logins can only read the last four digits of a credit
card number, whereas authorized logins can see all of the credit card
information.
JSON
Support
JSON
stands for Java Script Object Notation. With SQL Server 2016 you can now
interchange JSON data between applications and the SQL Server database
engine. By adding this support Microsoft has provided SQL Server the
ability to parse JSON formatted data so it can be stored in a relation
format. Additionally, with JSON support you can take relational data, and
turn it into JSON formatted data. Microsoft has also added some new
functions to provided support for querying JSON data stored in SQL Server.
Having these additional JSON features built into SQL Server should make it
easier for applications to exchange JSON data with SQL Server.
Multiple
TempDB Database Files
It
has been a best practice for a while to have more than one tempdb data file if
you are running on a multi-core machine. In the past, up through SQL
Server 2014, you always had to manually add the additional tempdb data files
after you installed SQL Server. With SQL Server 2016 you can now configure the
number of tempdb files you need while you are installing SQL Server.
Having this new feature means you will no longer need to manually add
additional tempdb files after installing SQL Server.
PolyBase
PolyBase
allows you to query distributed data sets. With the introduction of
PolyBase you will be able to use Transact SQL statements to query Hadoop, or
SQL Azure blob storage. By using PolyBase you can now write adhoc queries
to join relational data from SQL Server with semi-structured data stored in
Hadoop, or SQL Azure blob storage. This allows you to get data from
Hadoop without knowing the internals of Hadoop. Additionally you can
leverage SQL Server’s on the fly column store indexing to optimize your queries
against semi-structured data. As organizations spread data
across many distributed locations, PolyBase will be a solution for them to
leverage SQL Server technology to access their distributed semi-structured
data.
Query
Store
If
you are into examining execution plans than you will like the new Query Store
feature. Currently in versions of SQL Server prior to 2016 you can see
existing execution plans by using dynamic management views (DMVs). But,
the DMVs only allow you to see the plans that are actively in the plan
cache. You can’t see any history for plans once they are rolled out of
the plan cache. With the Query Store feature, SQL Server now saves
historical execution plans. Not only that but it also saves the query
statistics that go along with those historical plans. This is a
great addition and will allow you to now track execution plans performance for
your queries over time.
Row
Level Security
With
Row Level Security the SQL database engine will be able to restrict access to
row data, based on a SQL Server login. Restricting rows will be
done by filter predicates defined in inline table value function.
Security policies will ensure the filter predicates get executed for every
SELECT or DELETE operation. Implementing row level security at the
database layer means application developers will no longer need to maintain
code to restrict data from some logins, while allowing other logins to access
all the data. With this new feature, when someone queries a tables that
contains row level security they will not even know whether or not any rows of
data were filtered out.
R
Comes to SQL Server
With
Microsoft’s purchase of Revolution Analytics they are now able to incorporate R
to support advance analytics against big data right inside of SQL Server. By
incorporating R processing into SQL Server, data scientists will be able to
take their existing R code and run it right inside the SQL Server database
engine. This will eliminate the need to export your SQL server data in
order to perform R processing against it. This new feature brings R
processing closer to the data.
Stretch
Database
The
Stretch Database feature provides you a method to stretch the storage of your
On-Premise database to Azure SQL Database. But having the stretch
database feature allows you to have your most frequently accessed data stored
On-Premise, while your less accessed data is off-site in an Azure SQL
databases. When you enable a database to “stretch” the older data starts
moving over to the Azure SQL database behind the scenes. When you need to
run a query that might access active and historical information in a
“stretched” database the database engine seamlessly queries both the On-Premise
database as well as Azure SQL database and returns the results to you as if
they had come from a single source. This feature will make it easy for
DBA’s to archive information to a cheaper storage media without having to
change any actual application code. By doing this you should be able to
maximize performance on those active On-Premise queries.
Temporal
Table
A temporal table is table
that holds old versions of rows within a base table. By having temporal
tables SQL Server can automatically manage moving old row versions to the
temporal table every time a row in the base table is updated. The
temporal table is physically a different table then the base table, but is
linked to the base table. If you’ve been building or plan to build your
own method to managing row versioning then you might want to check out the new
temporal tables support in SQL server 2016 before you go forth and build your
own row versioning solution.
What’s New in SQL Server 2014 since SQL Server 2012
PERFORMANCE & SCALE
o In-Memory OLTP
o Enhanced In-Memory ColumnStore for DW
o Buffer Pool Extension to SSDs
o Enhanced Query Processing
o Resource Governor adds IO governance
o SysPrep at cluster level
o Predictable performance with tiering of compute, network, and storage with Windows Server 2012 R2
HIGH AVAILABILITY
o Enhanced AlwaysOn, with 8 secondaries and Replica Wizard
o Delayed Durability
o Clustered Shared Volume support, VHDX support (Windows Server 2012 R2)
o Manage on-premises and cloud apps (System Center 2012 R2)
SECURITY
o Enhanced separation of duty
o CC certification at High Assurance Level for 2014
o Backup encryption support
PROGRAMMABILITY
o Query optimization enhancements
EASY ACCESS TO DATA, BIG & SMALL
o Power Query
o Windows Azure HDInsight Service
o Analytics Platform System (PDW V2)
POWERFUL INSIGHTS WITH FAMILIAR TOOLS
o Power BI in Office 365
o Power Map for Excel
o Mobile interfaces for Power BI
HYBRID CLOUD SOLUTIONS
o Simplified backup to Windows Azure
o Support for backup of previous versions of SQL Server to Windows Azure
o Cloud back-up encryption support
o Simplified cloud Disaster Recovery with AlwaysOn replicas in Windows Azure VMs
EASY ON-RAMP TO THE CLOUD
o New Windows Azure Deployment UI
for SQL Server
for SQL Server
o Larger SQL Server VMs and memory sizes now available in Windows Azure
What’s New in SQL Server 2014 since SQL Server 2008 R2
PERFORMANCE & SCALE
o In-Memory OLTP
o Enhanced In-Memory ColumnStore for DW
o Support for 640 logical proc. & 4 TB memory
o Support to 15,000 partitions
o Resource Governor IO governance
o Buffer Pool Extension to SSDs
o Query optimization enhancements
o SysPrep at cluster level
o Predictable performance with tiering of compute, network, and storage with Windows Server 2012 R2
HIGH AVAILABILITY
o SQL Server AlwaysOn
o Delayed Durability
o Recovery Advisor
o Windows Server Core
o Live Migration
o Online Operations enhancements
o Clustered Shared Volume support, VHDX support (Windows Server 2012 R2)
o Manage on-premises and cloud apps (System Center 2012 R2)
SECURITY
o User-Defined Server Roles
o Default Schema for Groups
o SQL Server Audit
o SQL Server Fine-grained Auditing
o Enhanced separation of duty
o CC certification at High Assurance Level
o Backup encryption support
PROGRAMMABILITY
o SQL Server Data Tools
o Local DB runtime (Express)
o Data-tier Application Component project template
o Data-Tier Application Framework (DAC Fx)
o Query optimization enhancements
o Interoperability support (ADO.NET, ODBC, JDBC, PDO, ADO APIs and .NET C/C++, Java, Linux, and PHP platforms)
T-SQL ENHANCEMENTS
o Enhanced support for ANSI SQL standards
o Transact-SQL Static Code Analysis tools
o Transact-SQL code snippets
o Intellisense
o Unstructured & Complex Data Support
o FileTable built on FILESTREAM
o Remote Blob Storage with SharePoint 2010
o Statistical Semantic Search
o Spatial features, including Full Globe & arcs
o Large user-defined data types
MANAGEABILITY
o Distributed Replay
o Contained Database Authentication
o System Center Management Pack for SQL Server 2012
o Windows PowerShell 2.0 support
o Multi-server Management with SQL Server Utility Control Point
o Data-Tier Application Component
ACCESS ANY DATA
o Power Query
o Windows Azure HDInsight Service
o Analytics Platform System (PDW V2)
o Mash up data from different sources, such as Oracle & Hadoop
INSIGHTS WITH FAMILIAR TOOLS
o Power BI in Office 365
o Power Map for Excel
o Mobile interfaces for Power BI
COMPLETE BI SOLUTION
o SQL Server BI Edition
o HA for StreamInsight, complex event processing
o BI Semantic Model
o SQL Server Data Tools support for BI
o Change Data Capture for Oracle
ANALYSIS SERVICES
o Import PowerPivot models into Analysis Services
o Enhancements on productivity, performance
REPORTING SERVICES
o Power View
o Configurable reporting alerts
o Reporting as SharePoint Shared Service
o Report Builder 3.0
DATA QUALITY SERVICES
o Build organizational knowledge base
o Connect to 3rd party data cleansing providers
MASTER DATA SERVICES
o Master Data Hub
o Master Data Services Add-in for Microsoft Excel
INTEGRATION SERVICES
o Graphical tools in SSIS
o Extensible object model
o SSIS as a Server
o Broader data integration with more sources; DB vendors, cloud, Hadoop
o Pipeline improvements
HYBRID CLOUD SOLUTIONS
o Simplified backup to Windows Azure
o Support for backup of previous versions of SQL Server to Windows Azure
o Cloud back-up encryption support
o Simplified cloud Disaster Recovery with AlwaysOn replicas in Windows Azure VMs
EASY ON-RAMP TO THE CLOUD
o New Windows Azure Deployment UI for SQL Server
o Larger SQL Server VMs and memory sizes now available in Windows Azure
o DAC enhancements: Import/export with Windows Azure SQL Database
COMPLETE AND CONSISTENT
FROM ON-PREM TO CLOUD
o SQL Server Data Tools
o License Mobility (with SA)
o Resource Governor enhancements
o Snapshot backups to Windows Azure via SQL Server Management Studio
What’s New in SQL Server 2014 since SQL Server 2008
PERFORMANCE & SCALE
o In-Memory OLTP
o Enhanced In-Memory ColumnStore for DW
o Support for 640 logical proc. & 4 TB memory
o Support to 15,000 partitions
o Resource Governor IO governance
o Buffer Pool Extension to SSDs
o Query optimization enhancements
o SysPrep at cluster level
o Predictable performance with tiering of compute, network, and storage with Windows Server 2012 R2
o Data Compression with USC-2 Unicode support
o Backup Compression
HIGH AVAILABILITY
o SQL Server AlwaysOn
o Delayed Durability
o Recovery Advisor
o Windows Server Core
o Live Migration
o Online Operations enhancements
o Clustered Shared Volume support, VHDX support (Windows Server 2012 R2)
o Manage on-premises and cloud apps (System Center 2012 R2)
SECURITY
o User-Defined Server Roles
o Default Schema for Groups
o SQL Server Audit
o SQL Server Fine-grained Auditing
o Enhanced separation of duty
o CC certification at High Assurance Level
o Backup encryption support
PROGRAMMABILITY
o SQL Server Data Tools
o Local DB runtime (Express)
o Data-tier Application Component project template
o Data-Tier Application Framework (DAC Fx)
o Query optimization enhancements
o Interoperability support (ADO.NET, ODBC, JDBC, PDO, ADO APIs and .NET C/C++, Java, Linux, and PHP platforms)
T-SQL ENHANCEMENTS
o Enhanced support for ANSI SQL standards
o Transact-SQL Static Code Analysis tools
o Transact-SQL code snippets
o Intellisense
UNSTRUCTURED & COMPLEX DATA SUPPORT
o FileTable built on FILESTREAM
o Remote Blob Storage with SharePoint 2010
o Statistical Semantic Search
o Spatial features, including Full Globe & arcs
o Large user-defined data types
MANAGEABILITY
o Distributed Replay
o Contained Database Authentication
o System Center Management Pack for SQL Server 2012
o Windows PowerShell 2.0 support
o Multi-server Management with SQL Server Utility Control Point
o Data-Tier Application Component
ACCESS ANY DATA
o Power Query
o Windows Azure HDInsight Service
o Analytics Platform System (PDW V2)
o Mash up data from different sources, such as Oracle & Hadoop
INSIGHTS WITH FAMILIAR TOOLS
o Power BI in Office 365
o Power Map for Excel
o Mobile interfaces for Power BI
COMPLETE BI SOLUTION
o SQL Server BI Edition
o HA for StreamInsight, complex event processing
o BI Semantic Model
o SQL Server Data Tools support for BI
o Change Data Capture for Oracle
ANALYSIS SERVICES
o Import PowerPivot models into Analysis Services
o Enhancements on productivity, performance
REPORTING SERVICES
o Power View
o Configurable reporting alerts
o Reporting as SharePoint Shared Service
o Report Builder 3.0
DATA QUALITY SERVICES
o Build organizational knowledge base
o Connect to 3rd party data cleansing providers
MASTER DATA SERVICES
o Master Data Hub
o Master Data Services Add-in for Microsoft Excel
INTEGRATION SERVICES
o Graphical tools in SSIS
o Extensible object model
o SSIS as a Server
o Broader data integration with more sources; DB vendors, cloud, Hadoop
o Pipeline improvements
HYBRID CLOUD SOLUTIONS
o Simplified backup to Windows Azure
o Support for backup of previous versions of SQL Server to Windows Azure
o Cloud back-up encryption support
o Simplified cloud Disaster Recovery with AlwaysOn replicas in Windows Azure VMs
EASY ON-RAMP TO THE CLOUD
o New Windows Azure Deployment UI for SQL Server
o Larger SQL Server VMs and memory sizes now available in Windows Azure
o DAC enhancements: Import/export with Windows Azure SQL Database
COMPLETE AND CONSISTENT
FROM ON-PREM TO CLOUD
o SQL Server Data Tools
o License Mobility (with SA)
o Resource Governor enhancements
o Snapshot backups to Windows Azure via SQL Server Management Studio
What’s New in SQL Server 2014 since SQL Server 2005
PERFORMANCE & SCALE
o In-Memory OLTP
o Enhanced In-Memory ColumnStore for DW
o Support for 640 logical proc. & 4 TB memory
o Support to 15,000 partitions
o Resource Governor IO governance
o Buffer Pool Extension to SSDs
o Query optimization enhancements
o SysPrep at cluster level
o Predictable performance with tiering of compute, network, and storage with Windows Server 2012 R2
o Data Compression with USC-2 Unicode support
o Backup Compression
HIGH AVAILABILITY
o SQL Server AlwaysOn
o Database Mirroring
o Failover Clustering
o Database Snapshots
o Delayed Durability
o Recovery Advisor
o Windows Server Core
o Live Migration
o Online Operations
o Clustered Shared Volume support, VHDX support (Windows Server 2012 R2)
o Manage on-premises and cloud apps (System Center 2012 R2)
SECURITY
o User-Defined Server Roles
o Default Schema for Groups
o SQL Server Audit
o Transparent Data Encryption
o Extensible Key Management
o Standards-based Encryption
o SQL Server Fine-grained Auditing
o Enhanced separation of duty
o CC certification at High Assurance Level
o Backup encryption support
PROGRAMMABILITY
o SQL Server Data Tools
o Local DB runtime (Express)
o Data-tier Application Component project template
o Data-Tier Application Framework (DAC Fx)
o Query optimization enhancements
o Interoperability support (ADO.NET, ODBC, JDBC, PDO, ADO APIs and .NET C/C++, Java, Linux, and PHP platforms)
T-SQL ENHANCEMENTS
o Enhanced support for ANSI SQL standards
o Transact-SQL Static Code Analysis tools
o Transact-SQL code snippets
o Intellisense
DATA SUPPORT
o FILESTREAM data type
o FileTable built on FILESTREAM
o Remote Blob Storage with SharePoint 2010
o Spatial data support
o Full Text Search for unstructured files
o Statistical Semantic Search
o Large user-defined data types
PROGRAMMABILITY SUPPORT
o Support for LINQ and ADO.NET Entity Framework
o CLR Integration and ADO.NET Object Services
MANAGEABILITY
o Distributed Replay
o Contained Database Authentication
o System Center Management Pack for SQL Server 2012
o Windows PowerShell 2.0 support
o Multi-server Management with SQL Server Utility Control Point
o Data-Tier Application Component
o Multi-server Management with SQL Server Utility Control Point
o Data-Tier Application Component
o Policy-Based Management
o SQL Server Performance Data Collector
o Query enhancements
o SMTP mail for secure DB email w/o Outlook
ACCESS ANY DATA
o Power Query
o Windows Azure HDInsight Service
o Analytics Platform System (PDW V2)
o Mash up data from different sources, such as Oracle & Hadoop
INSIGHTS WITH FAMILIAR TOOLS
o Power BI in Office 365
o Power Map for Excel
o Mobile interfaces for Power BI
COMPLETE BI SOLUTION
o SQL Server BI Edition
o StreamInsight
o BI Semantic Model
o SQL Server Data Tools
o BI Development Studio
o Microsoft Visual Studio-based report dev tools
o Change Data Capture for Oracle
ANALYSIS SERVICES
o Import PowerPivot models into Analysis Services
o Enhancements on productivity, performance
o Cube design tools, block computations, and write-back to MOLAP
REPORTING SERVICES
o Power View
o Configurable reporting alerts
o Reporting as SharePoint Shared Service
o Report Builder 3.0
o Report Designer
o Report Manager
DATA QUALITY SERVICES
o Build organizational knowledge base
o Connect to 3rd party data cleansing providers
MASTER DATA SERVICES
o Master Data Hub
o Master Data Services Add-in for Microsoft Excel
INTEGRATION SERVICES
o Graphical tools in SSIS
o Extensible object model
o SSIS as a Server
o Broader data integration with more sources; DB vendors, cloud, Hadoop
o Pipeline improvements
o Persistent lookups
o High-performance connectors
o Data profiling tool
HYBRID CLOUD SOLUTIONS
o Simplified backup to Windows Azure
o Support for backup of previous versions of SQL Server to Windows Azure
o Cloud back-up encryption support
o Simplified cloud Disaster Recovery with AlwaysOn replicas in Windows Azure VMs
EASY ON-RAMP TO THE CLOUD
o New Windows Azure Deployment UI for SQL Server
o Larger SQL Server VMs and memory sizes now available in Windows Azure
o DAC enhancements: Import/export with Windows Azure SQL Database
COMPLETE AND CONSISTENT
FROM ON-PREM TO CLOUD
o SQL Server Data Tools
o License Mobility (with SA)
o Resource Governor enhancements
o Snapshot backups to Windows Azure via SQL Server Management Studio
This list also includes some technologies that work together with SQL Server such as Azure, System Center, Excel 2013, Power BI for Office 365 and others.
Collected information from Microsoft blog:
https://blogs.technet.microsoft.com/cansql/2014/04/13/sql-server-2014-benefits-of-upgrading-from-sql-server-2005-2008-2008r2-and-2012/
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