1. SQL Server 2014 In-Memory Overview
Nilabja Ball
Premier Field Engineer
Microsoft India

2. Nilabja Ball Premier Field Engineer with Microsoft India
10 years of SQL Server Experience
Speaker in SQL UG group, Microsoft Tech-Ed
Closely works with Mission Critical Tier 1 Microsoft Customers

3. Session Objectives And Takeaways
Tech Ready 15
9/18/2018
Session Objectives And Takeaways
Session Objective(s):
Understand SQL Server’s in-memory strategy
Be able to identify which technology will best help customers be successful
SQL Server has an integrated In-memory strategy that is more than isolated features
© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

4. SQL Server 2014 Investments
9/18/2018
SQL Server 2014 Investments
In-Memory Technologies
Enhanced
High Availability
New Hybrid
Scenarios
Other investments
In-Memory OLTP
5-25x performance gain for OLTP integrated into SQL Server
In-Memory DW
5-25x performance gain and high data compression
Updatable and clustered
SSD Bufferpool Extension
4-10X of RAM and up to 3X performance gain transparently for apps
Always On Enhancements
Increased availability and improved manageability of active secondaries
Online Database Operations
Increased availability for index/partition maintenance
Backup to Azure
Easy to implement and cost effective Disaster Recovery solution to Azure Storage
HA to Azure VM
Easy to implement and cost effective high availability solution with Windows Azure VM
Deploy to Azure
Deployment wizard to migrate database
Better together with Windows Server
WS2012 ReFS support
Online resizing VHDx
Hyper-V replica
Extending Power View
Enable Power View on existing analytic models and support new multi-dimensional models.
© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

5. SQL Server 2014 In-Memory Technology
9/18/2018
SQL Server 2014 In-Memory Technology
In-Memory Technologies
Applicable to
Transactional workloads:
Concurrent data entry, processing and retrieval
In-Memory OLTP
5-20X performance gain for OLTP integrated into SQL Server
In-Memory DW
5-25X performance gain and high data compression
Updatable and clustered
SSD Bufferpool Extension
4-10X of RAM and up to 3X performance gain transparently for apps
Applicable to
Decision support workloads:
Large scans and aggregates
Applicable to
Disk-based transactional workloads:
Large working (data)set
© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

6. Business Trends
Moore’s Law means more transistors and therefore cores, but…
CPU clock rate stalled…
Meanwhile RAM cost continues to drop
Chart reference
© 2014 Microsoft Corporation Microsoft Confidential

7. In-Memory OLTP Architectural Pillars
Principles
Performance-critical data fits in memory
Push decisions to compilation time
Conflicts are Rare
Built-In
Architectural Pillars
Main-Memory Optimized
T-SQL Compiled to Native Machine Code
Non-Blocking Execution
SQL Server Integration
Direct pointers to rows
Indexes exist only in memory
No buffer pool
No write-ahead logging
T-SQL compiled to machine code
Procedure and its queries, becomes a C function
Aggressive compile- time optimizations
Multi-version optimistic
Lock-free data structures
No locks, latches or spinlocks
Simple Management
Integrated queries & transactions
Integrated HA and backup/restore
Results
In-memory cache speed with capabilities of a database
Queries & business logic run at native-code speed
Transactions execute to completion without blocking
Hybrid engine and integrated experience

8. Memory-Optimized Tables
200, ∞
John
Beijing
Timestamps
Name
Chain ptrs
City
Row format
Hash index on City B P
BW-tree index on Name J S
100, 200
John
Paris
90,150
Susan
Bogota
50, ∞
Jane
Prague
70, 90
Susan
Brussels
Rows are multi-versioned, each has a valid time range indicated by two timestamps
A version is visible if transaction read time falls within the version’s valid time
Row can be part of multiple indexes, but there is only a single copy of the row

9. Create Database
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10. Create Memory Optimized Table
Hash Index
Collation BIN2
Range Index
This table is memory optimized
This table is durable
© 2014 Microsoft Corporation Microsoft Confidential

11. Natively Compiled Procedures
This proc is natively compiled
Native procs must be schema-bound
Execution context is required
Atomic blocks
Create a transaction if there is none
Otherwise, create a savepoint
Performing alter operations on natively compiled stored procedures is not supported as once again they are compiled into a DLL. One way to modify a natively compiled stored procedure is to drop and recreate the stored procedure:
Generate script for the permissions on the stored procedure.
Optional, generate script for the stored procedure and save as a backup.
Drop the stored procedure.
Create the altered stored procedure.
Re-apply the scripted permissions to the stored procedure.
Creation of a Natively compiled Stored procedure requires the following elements:
SCHEMABINDING
Natively compiled stored procedures must be bound to the schema of the objects it references. This means that table references by the procedure cannot be dropped. Tables referenced in the procedure must include their schema name, and wildcards (*) are not allowed in queries.
EXECUTE AS
Natively compiled stored procedures do not support EXECUTE AS CALLER, which is the default execution context. Therefore, specifying the execution context is required. The options EXECUTE AS OWNER, EXECUTE AS user, and EXECUTE AS SELF are supported.
BEGIN ATOMIC
The natively compiled stored procedure body must consist of exactly one atomic block. Atomic blocks guarantee atomic execution of the stored procedure. If the procedure is invoked outside the context of an active transaction, it will start a new transaction, which commits at the end of the atomic block. Atomic blocks in natively compiled stored procedures have two required options:
TRANSACTION ISOLATION LEVEL. See Transaction Isolation Levels for supported isolation levels.
LANGUAGE. The language for the stored procedure must be set to one of the available languages or language aliases.
Session settings are fixed at create time
© 2014 Microsoft Corporation Microsoft Confidential

12. Demo on In-Memory OLTP Table

13. SQL Engine With In-Memory

14. Types of candidate workloads
Application has OLTP characteristics
Relatively short transactions
High degree of concurrency, transactions from many sessions
Suited for in-memory processing
Critical path data can fit in memory
Currently encounter locking or latching bottlenecks
Code Characteristics
Stored procedures used
Code can be modified and isolated to subset of tables or stored procedures
© 2014 Microsoft Corporation Microsoft Confidential

15. Memory Optimized Table Limitations
No FOREIGN KEY and no CHECK constraints
No schema changes (ALTER TABLE) – need to drop/recreate table
No add/remove index – need to drop/recreate table
No DML triggers
No XML and no CLR data types
Rows are at most 8060 bytes – no off row data
No Large Object (LOB) types like varchar(max) .
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SQL Server 2014: In-Memory Overview

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