Actian ParAccel vs BigQuery comparison

"It has delivered results to our customers faster than we were able to previously."

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

"BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space."

"It's a stable, reliable solution."

"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."

"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."

"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."

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

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

"The stability needs work."

"I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."

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

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

"An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."

"We'd like to have more integrations with other technologies."

"It would be better if BigQuery didn't have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise, but in BigQuery, we have huge restrictions."

"The price is a bit high but the technology is worth it."

"The initial setup could be improved making it easier to deploy."

"The tool has competitive pricing."

"BigQuery is inexpensive."

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

"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."

"Price-wise, I think that is very reasonable."

"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."

"We are above the free threshold, so we are paying around 40 euros per month for BigQuery."

"BigQuery pricing can increase quickly. It's a high-priced solution."