Google has found a way to stretch a data warehouse across multiple data centers, using an architecture its engineers developed that could pave the way for much larger, more reliable and more responsive cloud-based analysis systems.Google's latest big-data tool is named as Mesa, which aims for speed.
For Google, Mesa solved a number of operational issues that traditional enterprise data warehouses and other data analysis systems could not. Google also needed a strong consistency for its queries, meaning a query should produce the same result from the same source each time, no matter which data center fields the query.
Mesa relies on a number of other technologies developed by the company, including the Colossus distributed file system, the BigTable distributed data storage system and the MapReduce data analysis framework. To help with consistency, Google engineers deployed a homegrown technology called Paxos, a distributed synchronization protocol.
In addition to scalability and consistency, Mesa offers another advantage in that it can run be run on generic servers, which eliminates the need for specialized, expensive hardware. As a result, Mesa can be run as a cloud service and easily scaled up or down to meet the job requirements.
Mesa is the latest in a series of novel data-processing applications and architectures that Google has developed to serve its business.