Hekaton is designed around four architectural principles

Hekaton, in contrast, is a row-based technology squarely focused on transaction processing (TP) workloads

1) Optimize for main memory data access: Storage-optimized engines (such as the current OLTP engine in SQL Server today) will retain hot data in a main memory buffer pool based upon access frequency. The data access and modification capabilities, however, are built around the viewpoint that data may be paged in or paged out to disk at any point. This perspective necessitates layers of indirection in buffer pools, extra code for sophisticated storage allocation and defragmentation, and logging of every minute operation that could affect storage. With Hekaton you place tables used in the extreme TP portion of an application in memory-optimized main memory structures. The remaining application tables, such as reference data details or historical data, are left in traditional storage optimized structures. This approach lets you memory-optimize hotspots without having to manage multiple data engines.

Hekaton’s main memory structures do away with the overhead and indirection of the storage optimized view while still providing the full ACID properties expected of a database system. For example, durability in Hekaton is achieved by streamlined logging and checkpointing that uses only efficient sequential IO.

 2) Accelerate business logic processing: Given that the free ride on CPU clock rate is over, Hekaton must be more efficient in how it utilizes each core. Today SQL Server’s query processor compiles queries and stored procedures into a set of data structures which are evaluated by an interpreter in SQL Server’s query processor. With Hekaton, queries and procedural logic in T-SQL stored procedures are compiled directly into machine code with aggressive optimizations applied at compilation time. This allows the stored procedure to be executed at the speed of native code.

3) Provide frictionless scale-up: It’s common to find 16 to 32 logical cores even on a 2-socket server nowadays. Storage-optimized engines rely on a variety of mechanisms such as locks and latches to provide concurrency control. These mechanisms often have significant contention issues when scaling up with more cores. Hekaton implements a highly scalable concurrency control mechanism and uses a series of lock-free data structures to eliminate traditional locks and latches while guaranteeing the correct transactional semantics that ensure data consistency.

4) Built-in to SQL Server: As I mentioned earlier – Hekaton is a new capability of SQL Server. This lays the foundation for a powerful customer scenario which has been proven out by our customer testing. Many existing TP systems have certain transactions or algorithms which benefit from Hekaton’s extreme TP capabilities. For example, the matching algorithm in financial trading, resource assignment or scheduling in manufacturing, or matchmaking in gaming scenarios. Hekaton enables optimizing these aspects of a TP system for in-memory processing while the cooler data and processing continue to be handled by the rest of SQL Server.

Author - Dave Campbell      Technical Fellow       Microsoft SQL Server