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Google Beefs Up BigQuery Big Data Tool

Google has unveiled a number of changes to BigQuery, its big data analytics tool that competes with Hadoop. It’s now easier to join and query multiple tables, which should save time for enterprises that use the service. Computerworld’s Joab Jackson reported, “Hoping to lure more Apache Hadoop users to its own data analysis services, Google […]

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Cynthia Harvey

Mar 15, 2013

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Google has unveiled a number of changes to BigQuery, its big data analytics tool that competes with Hadoop. It’s now easier to join and query multiple tables, which should save time for enterprises that use the service.

Computerworld’s Joab Jackson reported, “Hoping to lure more Apache Hadoop users to its own data analysis services, Google has outfitted BigQuery with the ability to query multiple data tables. ‘Joining terabyte-sized tables has traditionally been a challenging task for data analysts, requiring sophisticated MapReduce development skills, powerful hardware, or a lot of time — often all three,’ wrote Ju-kay Kwek, Google BigQuery product manager, in a blog post announcing the update. ‘Today with BigQuery you can get directly to business insights using SQL-like queries, with far less effort and far greater speed than you could before.'”

GigaOm’s Derrick Harris explained, “BigQuery is a cloud service that lets users analyze terabyte-sized data sets using SQL-like queries. It’s based on Google’s Dremel querying system, which can analyze data where it’s located (i.e., in the Google File System or BigTable) and which Google uses internally to analyze a variety of different data sets. Google claims queries in BigQuery run at interactive speeds, which is something that MapReduce — the previous-generation tool for dealing with such large data sets — simply couldn’t handle within a reasonable time frame or level of complexity. Of course, if you want to schedule batch jobs, BigQuery lets you do that, too, for a lower price.”

The Register’s Jack Clark added, “Google has updated its BigQuery cloud analytic service to make it attractive to people familiar with SQL. The new features for the analytics-as-a-service (AaaS) – Big JOIN, Big Group Aggregations, and support for the TIMESTAMP data type – were released by Google on Thursday. They are designed to cut the steps developers need to take in analysing large amounts of data, and make the technology easier to deal with.”

VentureBeat’s Christina Farr noted, “Google product manager Ju-kay Kwek announced the news on the company blog today, and claimed the new features will give businesses ‘new ways to work effectively with large amounts of data.’ More specifically, the updates give developers a greater range of query and data types, more flexibility with table structure, and an improved toolset for collaborative analysis.”