BigQuery vs IBM Db2 Warehouse comparison

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

"It's pretty stable. It's fast, and it is able to go through large quantities of data pretty quickly."

"What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."

"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."

"The solution is very useful nowadays for keeping a huge number of records."

"The feature called calibrating the capacity is valuable."

"When integrating their system into the cloud-based solutions, we were able to increase their efficiency and overall productivity twice compared with their on-premises option."

"BigQuery excels at data analysis. It processes vast amounts of information using its advanced architecture and sophisticated querying capabilities, making it crucial for critical insights and safe for handling sensitive data."

"I think it scales really well and as long as you take enough time to learn a little bit about it, it works really well."

"It can be mounted on the cloud, which is a huge plus. If the client, for example, starts small with on-premise deployment and then it rapidly needs to grow, we can transfer this to the cloud easily."

"The solution is stable."

"Provides good security and reliability."

"Some of the best features are stored procedures, parallelism, and different indexing strategies."

"The standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."

"The analytics engine is not bad at forecasting predictions."

"It can scale effectively as long as resources are available."

"It would be helpful if they could provide some dashboards where you can easily view charts and information."

"There are some limitations in the query latency compared to what it was three years ago."

"The solution should reduce its pricing."

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

"BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses."

"The product’s performance could be much faster."

"For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options."

"The main challenges are in the areas of performance and cost optimizations."

"In terms of improvement, IBM Db2 Warehouse should be more scalable."

"The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting."

"IBM Db2 Warehouse needs to improve its interface."

"Lacks sufficient documentation and particularly in Spanish."

"There were some initial challenges with IBM Db2 Warehouse about eight months ago when I worked in this environment. When I coordinated with IBM support, they mentioned that the memory was insufficient for our needs. Our business environment required significantly more memory than the previous cluster could provide. Consequently, we have worked closely with on-site IBM technical personnel to address this issue."

"Responding to support tickets takes a lot of time. It can range from two to four days, even for critical issues."

"The biggest challenge anyone could have with Db2 Warehouse is their references or online resources and documentation. They are very, very, very limited on the web."

"The biggest problems we have is when the backup solution is failing or slow and we run out of log space, which has happened probably a couple of times in the last four years."

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

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

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

"1 TB is free of cost monthly. If you use more than 1 TB a month, then you need to pay 5 dollars extra for each TB."

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

"Its cost structure operates on a pay-as-you-go model."

"The pricing is good and there are no additional costs involved."

"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."

"In a traditional on-prem database, in a data warehouse, the solution is probably on the expensive side."