BigQuery vs Infobright DB comparison

"BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI."

"The most valuable features of BigQuery is that it supports standard SQL and provides good performance."

"The product's most valuable features include its scalability and the ability to handle complex queries on large datasets."

"Its integration with other tools like Atlan through a Google Chrome extension is highly beneficial."

"The initial setup is simple."

"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."

"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."

"BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases."

"It has very amazing smart grid query feature for very fast aggregate queries across millions of rows"

"I rate BigQuery six out of 10 for affordability. It could be cheaper."

"They could enhance the platform's user accessibility."

"Some of the queries are complex and difficult to understand."

"The processing capability can be an area of improvement."

"When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming."

"The solution hinges on Google patterns so continued improvement is important."

"When I execute a query, the dashboard doesn't always present the output seamlessly. Troubleshooting requires opening each pipeline individually, which is time-consuming."

"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."

"Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk."

"I have tried my own setup using my Gmail ID, and I think it had a $300 limit for free for a new user. That's what Google is offering, and we can register and create a project."

"The price could be better. Usually, you need to buy the license for a year. Whenever you want more, you can subscribe to it, and you can use it. Otherwise, you can terminate the license. You can use it daily or monthly, and we use it based on a project's requirements."

"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."

"One terabyte of data costs $20 to $22 per month for storage on BigQuery and $25 on Snowflake. Snowflake is costlier for one terabyte, but BigQuery charges based on how much data is inserted into the tables. BigQuery charges you based on the amount of data that you handle and not the time in which you handle it. This is why the pricing models are different and it becomes a key consideration in the decision of which platform to use."

"The solution's pricing is cheaper compared to other solutions."

"The product operates on a pay-for-use model. Costs include storage and query execution, which can accumulate based on data volume and complexity."

"The pricing is adaptable, ensuring that organizations can tailor their usage and costs based on their specific requirements and configurations within the Google Cloud Platform."

"The pricing appears to be competitive for the intended usage scenarios we have in mind."

"Our pricing was based on server instances and it was actually very cheap compared to Oracle. I guess you get what you pay for."