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Google has revamped its cloud-hosted BigQuery analytics service with features that the company says makes it more powerful and easy to use.
BigQuery lets enterprise run batch and real-time data analytics applications against really massive data sets.
Google itself describes it as a “No-Ops analytics database” that is designed to scale in seconds, requires little instance or cluster management and lets businesses pay only for the services they consume.
With the latest update, Google has added new features such as User Defined Functions (UDFs), support for increased query limits and several improvements to its user interface.
UDFs are designed to give administrators more flexibility in situations where computations are difficult or even downright impossible to express in SQL, according to Thomas Park, a senior software engineer with Google’s BigQuery team.
UDFs “give you the ability to combine the convenience and accessibility of SQL with the option to use a familiar programming language, JavaScript, when SQL isn’t the right tool for the job,” Park noted in a blog post Tuesday. UDFs make it easier to express complex conditional logic in queries in situations where SQL cannot.
As part of the enhancements, users also are now able to run queries against their data without loading the files first into BigQuery, Google noted it its separate blog post announcing the updates. The new functionality simplifies data imports into BigQuery and allows queries to be written directly to cloud storage files, the company said.
The increased query limit size in the latest update gives BigQuery customers greater flexibility in working with their applications. Businesses are now allowed to submit up to 50 simultaneous queries against their data, compared to the 20 they were allowed previously.
Similarly, they now have a cap of 100,000 queries per day compared to the 20,000 that were permitted previously. Some other limits pertaining to the number of bytes processed and the size of queries have also been removed as part of an effort to give businesses more freedom within the BigQuery environment, Google noted in its blog.
Google added a new dynamic query optimization feature and enhancements to the core query execution engine to ramp up BigQuery’s performance and scalability. The company also added some features that it says have made BigQuery more open. For example, a BigQuery Slots feature now allows business to expand and allot the resources they can tap while running a particular query.
These latest updates continue Google’s efforts to make BigQuery the cloud-hosted engine of choice for enterprises looking to run large analytics applications.
Earlier this year, the company introduced support for faster data streaming and several new security controls designed to meet enterprise security requirements.
The company also entered into several strategic partnerships with vendors of Extract, Transform, Load (ETL) tools as part of a bid to give enterprise more choice for preparing their data for use in BigQuery.
These vendors include Talend, SnapLogic and xPlenty. Google also has partnerships with another group of vendors including Bime, Looker and Tableau that give businesses a way to build more visually interactive and user-friendly front ends to BigQuery.