The management interface in BigQuery is very convenient — it’s easy to query tables, locate datasets, access query history and rerun past queries, and the product integrates seamlessly with many other tools. Review collected by and hosted on G2.com.

- It is very hard to predict the costs- this tool is collaborative and many people in the organization have access-users may run heavy JOINs or use SELECT *, which significantly increases the amount of data scanned

-There were several use cases that required millisecond-level response times, and BigQuery is less suitable for those scenarios.

-Although I really like the interface, it’s very difficult to manage the data at a high level , for example, handling schema versioning is quite challenging. Review collected by and hosted on G2.com.

It is the best data storage platforms available on cloud. It has a number of features that are easy to use and simple to implement. Our company uses it frequently as we deal with a lot of customer data and analytics. Google's customer support is top notch as we expect of it. Review collected by and hosted on G2.com.

I have been using it for a while now and I have no dislikes yet. Review collected by and hosted on G2.com.

There are too many options to connect within the Google ecosystem, and the pricing is great. Review collected by and hosted on G2.com.

Can become expensive with large or inefficient queries, cost controls need careful setup, and performance tuning is less transparent than traditional databases. Review collected by and hosted on G2.com.

The possibility to make queries and connect data from different sources together in one simple query Review collected by and hosted on G2.com.

Some basic reference functions cannot be used and I need to create several CTE or write several time the same code just to get multiple views or connections within columns Review collected by and hosted on G2.com.

Super fast querying of huge amounts of data, ondemand without having to manage servers Review collected by and hosted on G2.com.

just that minimum query speed forr tiny amounts of data Review collected by and hosted on G2.com.

I like best about Google Cloud BigQuery is how it lets you analyze massive datasets extremely fast with almost zero infrastructure management. Review collected by and hosted on G2.com.

BigQuery charges based on the amount of data scanned per query. Inefficient queries (like SELECT *) can quickly increase costs.

Why this is a problem: You must be very careful with query optimization and cost monitoring. Review collected by and hosted on G2.com.

As it supports serverless, the complications to set up a server are reduced. Regular use and practice for big data for beginners is very useful. Many complicated settings are reduced. As part of learning for data engineering, it's been the most useful platform for me. It's very fast, easy to integrate with other databases. Review collected by and hosted on G2.com.

The free trial has to be increased or should be limited for some complex tasks and give minimum server options for learning. The cost is very high and some integrations with other clouds are not easy as it mainly supports Google platforms only. Customer support is not very responsive for the free trial. Review collected by and hosted on G2.com.

That I can quickly query data and share queries with my team Review collected by and hosted on G2.com.

Integration with Google drive is unstable Review collected by and hosted on G2.com.

Big query is fast and feels very effortless, though I have a huge amount of data and it provides me answers in seconds which is one of the big things I liked in Google Cloud Big Query and the other thing is the workspace is neat and easy to navigate for me even when I'm using it for the first time. Review collected by and hosted on G2.com.

When I'm using big query in my initial days, If I accidentally ran any big query without any alert the query is ran and it costed me a lot and also, we don't see how data is processed and if something went wrong it is hard to figure out. Review collected by and hosted on G2.com.

The company that I worked for, used Google Cloud BigQuery as it's Data Warehouse solution and selected it post comparisons with Snowflake. Primary reason for it being it's a fully managed, serverless database which allowed us to analyze large scale datasets using SQL. The best part was the cost proposition for BigQuery compared to similar tools/products on the market since it offers pay/query approach. More queries = more money and vice-versa. Also, with this being a Google product, there is an integration option with ML models which always helps in this day and age. Review collected by and hosted on G2.com.

* Latency: If you tend to run long, complex queries - latency creeps in which tends to really hamper the performance.

* Data Transfer fees: something teams often tend to overlook is data transfer fees. Moving large datasets in/out of BigQuery can rack up large fees which need to be tracked and factored into your spending analysis.

* Issues with Stored procedures: our Database teams reported a lot of issues with old-school stored procedures and highlighted that BigQuery may have SQL support, however, it's not great for complex Stored procedures. Review collected by and hosted on G2.com.