Enabling Growth Through Performance
Enabling Growth Through Performance

SQL Server Memory-Optimized Tables

Leveraging In-Memory Technology for Improved Performance


SQL Server’s memory-optimized tables, introduced in SQL Server 2014, are designed to significantly improve performance by leveraging in-memory technology. These tables store data directly in memory, enabling faster access and reducing the need for disk-based storage. In this article, we will explore memory-optimized tables, their benefits, and how to create and manage them in SQL Server.

Benefits of Memory-Optimized Tables

Enhanced performance: Memory-optimized tables provide faster data access, as they reside entirely in memory, eliminating the need for disk-based storage and reducing I/O latency. This results in improved query performance, making them ideal for scenarios with high transaction rates or real-time data processing.

Reduced contention: Traditional disk-based tables may experience performance degradation due to contention issues, such as lock and latch contention. Memory-optimized tables employ a lock-free and latch-free design, enabling concurrent access without blocking, which reduces contention and boosts performance.

Optimized data structures: Memory-optimized tables use a different data structure than traditional disk-based tables. They employ a row-versioning system that eliminates the need for locks and latches, further improving concurrency and throughput.

Streamlined maintenance: Memory-optimized tables reduce the need for index and table maintenance, as their index structures are optimized for in-memory storage and do not suffer from fragmentation.

There are a few important points to consider when managing memory-optimized tables:

1. Durability options: Memory-optimized tables can be created with two durability options: SCHEMA_AND_DATA (default) and SCHEMA_ONLY. SCHEMA_AND_DATA ensures that both the table schema and data are persisted on disk, while SCHEMA_ONLY only persists the schema. The SCHEMA_ONLY option provides even faster performance but at the cost of data loss in case of a server restart or crash.

2. Indexing: Memory-optimized tables support hash and nonclustered indexes. Hash indexes are optimized for point lookups and can deliver better performance for certain workloads. Nonclustered indexes, on the other hand, are optimized for range queries.

3. Limitations: Memory-optimized tables have some limitations compared to traditional disk-based tables. For example, they do not support foreign key constraints, identity columns, or triggers. Additionally, the ALTER TABLE statement is not supported for memory-optimized tables, so schema changes require recreating the table.

4. Monitoring and capacity planning: Ensure that you have enough memory available on your SQL Server instance to accommodate memory-optimized tables. Monitor memory usage using tools such as the Vroom Performance Suite and plan capacity accordingly to avoid running out of memory, which can impact the performance of both memory-optimized and traditional tables.

Creating Memory-Optimized Tables

To create a memory-optimized table in SQL Server, you must first create a memory-optimized filegroup and add a container to store the memory-optimized data. Then, you can create the memory-optimized table using the CREATE TABLE statement with the MEMORY_OPTIMIZED = ON option.

Create a memory-optimized filegroup:


Add a container to the filegroup:

ADD FILE (NAME = 'YourContainerName', FILENAME = 'C:\YourFilePath\YourContainerName_directory')
TO FILEGROUP YourFileGroupName;

Create a memory-optimized table:

CREATE TABLE dbo.YourMemoryOptimizedTableName
    Column2 NVARCHAR(50) NOT NULL,

The DURABILITY option specifies the durability level for the memory-optimized table. There are two options:

SCHEMA_AND_DATA (default): Provides full durability for both schema and data. Changes to the table schema and data are persisted on disk and survive server restarts.

SCHEMA_ONLY: When SQL Server is restarted, the schema survives but all data which resides in the table is lost.

Use Cases for Memory-Optimized Tables

Memory-optimized tables are particularly well-suited for the following scenarios:

High-concurrency workloads: Applications with a high volume of concurrent transactions, such as e-commerce platforms, can benefit from memory-optimized tables’ reduced contention and improved throughput.

Real-time analytics: Memory-optimized tables enable faster data retrieval and aggregation, making them ideal for real-time analytics and reporting applications.

Caching: Storing frequently accessed data in memory-optimized tables can serve as an efficient caching mechanism to reduce I/O overhead and improve application performance.

Session state management: Memory-optimized tables can be used to manage session state in web applications, allowing for faster session data retrieval and updates.

Temporal data storage: Applications that process short-lived data, such as data streams or message queues, can leverage memory-optimized tables for faster processing and reduced latency.


Memory-optimized tables in SQL Server offer a powerful solution for enhancing performance and scalability in high-concurrency and real-time analytics scenarios. By understanding the benefits, use cases, and management considerations, organizations can effectively leverage memory-optimized tables to improve application performance and meet growing data processing demands.

Closing Thoughts

The next person that makes the blanket statement that “RAM is cheap” has to send me some. That is all…

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