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The SQL Server System Overview document provides an overview of the client and server protocols that are used by Microsoft SQL Server. This document covers protocols that are commonly shared by SQL Server components and those protocols that are used only by specific components. Where appropriate, this document describes the relationships between protocols and provides example scenarios to show how they are used.
SQL Server is a data platform that includes several data management and analysis technologies. This document covers those elements of the platform that require protocols that interoperate.
Master Data Services: The Master Data Services (MDS) service and API provide a service-oriented design architecture (SOA) that encapsulates and modularizes the internal workings of SQL Server, in addition to a standard API to interact and integrate with SQL Server Master Data Services. The SQL Server MDS framework ensures that the internal functions of the product are better modularized to support both an API and a modular component development. For more information, see [MSDN-MDS].
Reporting Services: Reporting Services delivers enterprise, web-enabled reporting functionality for creating reports that draw content from a variety of data sources, for publishing reports in various formats, and for centrally managing security and subscriptions. For more information, see [MSDN-SSRS].
Analysis Services: Analysis Services supports high performance analytical applications by enabling an implementer to design, create, manage, and query Multidimensional and Tabular data models. For more information, see [MSDN-ASMD].
Database Engine: The Database Engine is the core service for storing, processing, and securing data. The Database Engine provides controlled access and rapid transaction processing to meet the requirements of the most demanding data-consuming applications within an enterprise. The Database Engine also provides rich support for sustaining high availability. For more information, see [MSDN-SSDBEng].
Complex event processing: Complex event processing (CEP) is the continuous and incremental processing of event (data) streams from multiple sources based on declarative query and pattern specifications with near-zero latency. The goal is to identify meaningful patterns, relationships, and data abstractions from among seemingly unrelated events and to trigger immediate response actions. Typical event stream sources include data from manufacturing applications, financial trading applications, web analytics, and operational analytics. The CEP Engine provides a dedicated web service to handle requests from client applications for managing the system.
Big data clusters: Big data clusters provide the ability to deploy scalable clusters of SQL Server containers that can combine and analyze high-value relational data with high-volume big data. This flexibility of interaction with big data lets the user query external data sources, store big data in external file systems managed by SQL Server, or query data from multiple external data sources through the cluster. For more information, see [MSDOCS-SSBDC].
To deliver these functionalities, SQL Server uses eight major sets of technologies:
Network connectivity and application development
Master Data Services
Reporting Services
Analysis Services
Database Engine
Complex event processing engine
Manageability
Big data clusters
This document provides an overview of the protocols that can be used by one or more of the SQL Server products that are listed in Microsoft Implementations (section 4). Specific release information for each protocol is indicated in the individual technical specifications only, unless otherwise indicated in the summary information provided in section 2.2.