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Google's Big-Data Tool, Mesa, Holds Petabytes of Data Across Multiple Servers

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Google says its big-data architecture, Mesa, can store petabytes of data, update millions of rows of data per second, and field trillions of queries daily across multiple servers, enabling continuous operation of the data warehouse even if a data center fails. "Mesa ingests data generated by upstream services, aggregates and persists the data internally, and serves the data via user queries," note Google researchers. They say Mesa was originally constructed to house and analyze critical measurement data for Google's Internet advertising business, but the technology could be applicable to other, similar data warehouse tasks.

Mesa is dependent on other Google technologies, such as the Colossus distributed file system, the BigTable distributed data storage system, and the MapReduce data analysis framework. Google engineers implemented Paxos, a distributed synchronization protocol, to help address query consistency issues. Mesa also can operate on generic servers, making costly specialized hardware unnecessary and enabling Mesa to be run as a cloud service with the advantage of scalability.

Consultant Curt Monash suggests Mesa may face limited future commercial prospects, and he recommends enterprises seek commercial or open source options to maintain data warehouse consistency across data centers before adopting Google's offerings. He says the majority of new data stores under development boast some form of multi-version currency control.

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