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AbstractBigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects

2 Data ModelA Bigtable is a sparse, distributed, persistent multidimensional sorted map. The map is indexed by a row key, column key, and a timestamp; each value in the map is an uninterpreted a

3 APIThe Bigtable API provides functions for creating and deleting tables and column families. It also provides functions for changing cluster, table, and column family metadata, such as access co

4 Building BlocksBigtable is built on several other pieces of Google infrastructure. Bigtable uses the distributed Google File System (GFS) to store log and data files. A Bigtable cluster typica

5 ImplementationThe Bigtable implementation has three major components: a library that is linked into every client, one master server, and many tablet servers. Tablet servers can be dynamically

8 Real ApplicationsAs of August 2006, there are 388 non-test Bigtable clusters running in various Google machine clusters, with a combined total of about 24,500 tablet servers. Table 1 shows a

9 LessonsIn the process of designing, implementing, maintaining,and supporting Bigtable, we gained useful experience and learned several interesting lessons.One lesson we learned is that large dis

10 Related WorkThe Boxwood project [24] has components that overlap in some ways with Chubby, GFS, and Bigtable, since it provides for distributed agreement, locking, distributed chunk storage, and

11 ConclusionsWe have described Bigtable, a distributed system for storing structured data at Google. Bigtable clusters have been in production use since April 2005, and we spent roughly seven per