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Tableau - Architecture of tableau

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asked Ramesshh November 1, 2014 01:35 AM  

Tableau has a highly scalable, n-tier client-server architecture that serves mobile clients, web clients and desktop-installed software. Tableau Desktop is the authoring and publishing tool that is used to create shared views on Tableau Server Tableau Server is an enterprise-class business analytics platform that can scale up to hundreds of thousands of users. It offers powerful mobile and browser-based analytics and works with a company’s existing data strategy and security protocols. Tableau Server: • Scales up: Is multi-threaded • Scales out: Is multi-process enabled • Provides integrated clustering • Supports High Availability • Is secure • Runs on both physical and Virtual Mach Below, we explain each of the layers, starting with customer data. Data Layer One of the fundamental characteristics of Tableau is that it supports your choice of data architecture. Tableau does not require your data to be stored in any single system, proprietary or otherwise. Most organizations have a heterogeneous data environment: data warehouses live alongside databases and Cubes, and flat files like Excel are still very much in use. Tableau can work with all of these simultaneously. You do not need to bring all your data in-memory unless you choose to. If your existing data platforms are fast and scalable, Tableau allows you to directly leverage your investment by utilizing the power of the database to answer questions. If this is not the case, Tableau provides easy options to upgrade your data to be fast and responsive with our fast in-memory Data Engine. Data Connectors Tableau includes a number of optimized data connectors for databases such as Microsoft Excel, SQL Server, Oracle, Teradata, Vertica, Cloudera Hadoop, and many more. There is also a generic ODBC connector for any systems without a native connector. Tableau provides two modes for interacting with data: Live connection or In-memory. Users can switch between a live and in-memory connection as they choose. Live connection: Tableau’s data connectors leverage your existing data infrastructure by sending dynamic SQL or MDX statements directly to the source database rather than importing all the data. This means that if you’ve invested in a fast, analytics-optimized database like Vertica, you can gain the benefits of that investment by connecting live to your data. This leaves the detail data in the source system and send the aggregate results of queries to Tableau. Additionally, this means that Tableau can effectively utilize unlimited amounts of data – in fact Tableau is the front-end analytics client to many of the largest databases in the world. Tableau has optimized each connector to take advantage of the unique characteristics of each data source. In-memory: Tableau offers a fast, in-memory Data Engine that is optimized for analytics. You can connect to your data and then, with one click, extract your data to bring it in-memory in Tableau. Tableau’s Data Engine fully utilizes your entire system to achieve fast query response on hundreds of millions of rows of data on commodity hardware. Because the Data Engine can access disk storage as well as RAM and cache memory, it is not limited by the amount of memory on a system. There is no requirement that an entire data set be loaded into memory to achieve its performance goals. Tableau Server Components The work of Tableau Server is handled with the following four server processes: Application Server: Application Server processes (wgserver.exe) handle browsing and permissions for the Tableau Server web and mobile interfaces. When a user opens a view in a client device, that user starts a session on Tableau Server. This means that an Application Server thread starts and checks the permissions for that user and that view. VizQL Server: Once a view is opened, the client sends a request to the VizQL process (vizqlserver.exe). The VizQL process then sends queries directly to the data source, returning a result set that is rendered as images and presented to the user. Each VizQL Server has its own cache that can be shared across multiple users. Data Server: The Tableau Data Server lets you centrally manage and store Tableau data sources. It also maintains metadata from Tableau Desktop, such as calculations, definitions, and groups. The published data source can be based on: • A Tableau Data Engine extract • A live connection to a relational database (cubes are not supported) Read more about the Data Server in the section Data Strategy below. Backgrounder: The backgrounder refreshes scheduled extracts and manages other background tasks


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