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Bigtable: A Distributed Storage System for Structured Data
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ACM Transactions on Computer Systems (TOCS) archive
Volume 26 ,  Issue 2  (June 2008) table of contents
Article No. 4  
Year of Publication: 2008
ISSN:0734-2071
Authors
Fay Chang  Google, Inc.
Jeffrey Dean  Google, Inc.
Sanjay Ghemawat  Google, Inc.
Wilson C. Hsieh  Google, Inc.
Deborah A. Wallach  Google, Inc.
Mike Burrows  Google, Inc.
Tushar Chandra  Google, Inc.
Andrew Fikes  Google, Inc.
Robert E. Gruber  Google, Inc.
Publisher
ACM  New York, NY, USA
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ABSTRACT

Bigtable 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 at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). Despite these varied demands, Bigtable has successfully provided a flexible, high-performance solution for all of these Google products. In this article, we describe the simple data model provided by Bigtable, which gives clients dynamic control over data layout and format, and we describe the design and implementation of Bigtable.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Fay Chang: colleagues
Jeffrey Dean: colleagues
Sanjay Ghemawat: colleagues
Wilson C. Hsieh: colleagues
Deborah A. Wallach: colleagues
Mike Burrows: colleagues
Tushar Chandra: colleagues
Andrew Fikes: colleagues
Robert E. Gruber: colleagues