NOTE: GrowthBeat tickets go up $200 this Friday at 5pm Pacific. VentureBeat is gathering the best and brightest in modern digital marketing to help declutter the landscape, simplify the functions, clarify the goals, and point the way to success. Get the full scoop here, and register by Friday to save!
Google’s BigQuery application has launched into general availability with an aim to help businesses crunch “big data” sets easier and cheaper than ever, the company said Tuesday.
BigQuery, as we previously detailed in November, gives companies of all sizes a powerful cloud-based tool to analyze data. Traditionally, crunching big data sets has taken more IT investment than simply spinning up and uploading data to a Software-as-a-Service (SaaS) program.
The SaaS software stands in stark contrast to open-source data software Hadoop and companies like Cloudera that help companies get a handle on Hadoop. It’s also quite different from on-premise data crunching software like HP-owned Vertica and IBM-owned Netezza.
Google product manager Ju-kay Kwek, who is overseeing the company’s big data efforts, told me companies that rely on data and business intelligence would likely prefer BigQuery over other options because it’s easier to set up and it costs less.
“On-premise options like Netezza and Vertica are fast and powerful, but they will cost you,” Kwek said. “And with Hadoop, you need more heads and you have to build out a custom Hadoop system.”
Kwek said one of Google’s largest advertising customers used BigQuery verus its own on-premise Hadoop cluster as a test to see how well it worked. BigQuery crunched the data ten times faster, showing how much faster data crunching can be when using Google’s monstrous computing power.
While in limited preview, BigQuery was free to try for 30 days, but now that the service is all the way live, companies will have to pony up. Thankfully, the prices appear fairly reasonable. Here’s the breakdown:
Let us know in the comments if your company might give BigQuery a shot for its big data needs or if you prefer Hadoop, Netezza, or Vertica.
Data image: Toria/Shutterstock