Google has added some new capabilities to Google BigQuery, its cloud-based analytics platform, including the ability to aggregate large numbers of distinct values, as well as native support for importing and querying Timestamp data. A third new feature, Big JOIN, allows users to “join very large datasets at interactive speeds” via SQL-like queries, according to Google. As an example, the technology allowed one of Google’s internal teams to merge 27 TB of usage data with 10GB of configuration data within 60 seconds; the aggregation feature (known as Big Group Aggregations) then allowed them to segment off the resulting dataset by customer. “With these capabilities, you will now be able to join and perform aggregate analysis on multi-terabyte datasets using SQL-like queries or integrated 3rd party tools, instead of having to initiate complex coding projects,” Ju-kay Kwek, product manager for BigQuery, wrote in a March 14 posting on the Official Google Enterprise Blog. “Pricing remains the same: you pay only for the actual data that’s processed by your queries.” Google released BigQuery to the public in May 2012, after months of limited previews. The cloud service lets users crunch massive datasets—one of its original selling points was the ability to scale to trillions of records, while providing secure SSL access and group- and user-based permissions via Google accounts. The platform was meant to handle massive amounts of data better than Google Cloud SQL, the search-engine giant’s hosted MySQL instance. “In Google World, BigQuery is an enterprise play, which to them means more than 15 people involved,” Ray Wang, principal analyst and CEO of Constellation Research, said in an interview with SlashBI when BigQuery was first released. “They’re democratizing Big Data for smaller companies.” Indeed, Google’s own blog posting alluded to BigQuery’s ability to serve up data analytics at significantly less resource cost. “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,” it read. “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.” All full BigQuery FAQ is available on Google’s Developers Website. Image: Google Google Adds New Capabilities to BigQuery
Google has added some new capabilities to Google BigQuery, its cloud-based analytics platform, including the ability to aggregate large numbers of distinct values, as well as native support for importing and querying Timestamp data. A third new feature, Big JOIN, allows users to “join very large datasets at interactive speeds” via SQL-like queries, according to Google. As an example, the technology allowed one of Google’s internal teams to merge 27 TB of usage data with 10GB of configuration data within 60 seconds; the aggregation feature (known as Big Group Aggregations) then allowed them to segment off the resulting dataset by customer. “With these capabilities, you will now be able to join and perform aggregate analysis on multi-terabyte datasets using SQL-like queries or integrated 3rd party tools, instead of having to initiate complex coding projects,” Ju-kay Kwek, product manager for BigQuery, wrote in a March 14 posting on the Official Google Enterprise Blog. “Pricing remains the same: you pay only for the actual data that’s processed by your queries.” Google released BigQuery to the public in May 2012, after months of limited previews. The cloud service lets users crunch massive datasets—one of its original selling points was the ability to scale to trillions of records, while providing secure SSL access and group- and user-based permissions via Google accounts. The platform was meant to handle massive amounts of data better than Google Cloud SQL, the search-engine giant’s hosted MySQL instance. “In Google World, BigQuery is an enterprise play, which to them means more than 15 people involved,” Ray Wang, principal analyst and CEO of Constellation Research, said in an interview with SlashBI when BigQuery was first released. “They’re democratizing Big Data for smaller companies.” Indeed, Google’s own blog posting alluded to BigQuery’s ability to serve up data analytics at significantly less resource cost. “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,” it read. “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.” All full BigQuery FAQ is available on Google’s Developers Website. Image: Google