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 provides a scalable solution for creation and delivery of web, mobile and desktop analytics.
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 Machines
Tableau Server architecture supports fast and flexible deployments
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Data Layer: 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. If your existing data platforms are fast and scalable.
Data Connectors: Tableau includes some optimized data connectors for databases such as Microsoft Excel, SQL Server, Oracle, Teradata, Vertica, Cloudera, Hadoop, and much 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: 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.
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.
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