Google Cloud BigQuery Reviews & Product Details

What I like most about BigQuery is that I can work with large amounts of data without worrying too much about managing servers or infrastructure. Running SQL queries is straightforward, and even when working with bigger datasets, the results usually come back quickly. I also like how easily it connects with other Google Cloud services. It makes data analysis much simpler and saves a lot of time compared to handling everything manually. Review collected by and hosted on G2.com.

One thing I find less helpful is that BigQuery costs can become difficult to manage if queries are not optimized properly. Beginners may also need some time to understand the pricing, permissions, and overall setup. The interface can feel a bit overwhelming at first, especially for someone who is new to Google Cloud. Review collected by and hosted on G2.com.

I like how easy it is to query huge amounts of data without worrying about managing infrastructure. I use BigQuery quite a bit for debugging, analyzing usage patterns, and pulling data for internal tools. Being able to run SQL queries across millions of rows and get results in seconds is super useful. It also works well with the rest of Google Cloud, which makes connecting different data sources pretty straightforward. Review collected by and hosted on G2.com.

The biggest issue for me is how easy it is to accidentally run expensive queries. If you're not careful with how much data you're scanning, costs can add up pretty quickly. The UI also feels a bit cluttered at times, especially when working with multiple datasets. Debugging slow queries could be easier too, since it's not always obvious what's causing the slowdown. Review collected by and hosted on G2.com.

Google Cloud BigQuery is incredibly easy to set up. The UI is clear and intuitive, and the Google Cloud platform overall has, in my experience, the best interface among the major providers. The integration with LLMs has also been fantastic, making it easier to connect everything and start seeing immediate ROI. Pricing is more than fair. Review collected by and hosted on G2.com.

There’s still a bit of a learning curve, but overall it’s the most beginner-friendly cloud platform I’ve used. Review collected by and hosted on G2.com.

We use BigQuery as our primary data warehouse, and it's been quite reliable for handling large volumes of data from different sources. I particularly like how easy it is to query data using SQL without having to worry too much about managing the underlying infrastructure.

It integrates really well with other GCP services like Cloud Storage, Cloud Functions and Dataform, which makes building and maintaining data pipelines much easier. The UI is fairly straightforward, and features like scheduled queries, partitioning and clustering are useful for managing large datasets and improving query performance. Review collected by and hosted on G2.com.

One thing I find a bit frustrating is the slot-based pricing and capacity management. While having dedicated slots can be useful, understanding how many slots are actually needed and managing slot reservations can get complicated. It's not always straightforward to decide between on-demand pricing and capacity-based pricing, especially when workloads vary throughout the day. I also feel that monitoring slot utilisation and optimising costs could be made simpler and more intuitive. Review collected by and hosted on G2.com.

I use Google Cloud BigQuery as our primary data warehouse for data from across the organization. I like that it lets us join data from many group businesses and their sources that we otherwise couldn’t use in combination. It’s easy to use and has a familiar SQL-like interface. Querying data from diverse sources feels like writing a query against one Postgres database and doesn’t require reskilling. Review collected by and hosted on G2.com.

I find the fully qualified table names a bit verbose, though it’s really a non-issue. I’d like to be able to alias them uniquely to my account, so I can use a simple name like Products instead of project-dataset.Products. Review collected by and hosted on G2.com.

It’s easy to use, and it’s available on the cloud, so it doesn’t take up hardware space. The best part is that we have the option to save our queries and share them as well. Review collected by and hosted on G2.com.

It’s mainly familiar with BigQuery, since its native environment is Google Cloud. Sometimes queries run slowly, especially when working with complex tables. By default, we can only see the first 50 rows, and it really should show more. Also, when we copy the output, we’re only able to copy some of the records instead of the full result set. We can append records, but we can’t update or delete them. Review collected by and hosted on G2.com.

Really Fast columnar queries easy to manage and connect with google services such as adds or google play store Review collected by and hosted on G2.com.

Pricing model. The cost of big query can scale super fast especially in self serve analytics teams like mine Review collected by and hosted on G2.com.

BigQuery is our data warehouse and everything runs through it. We load product data from Mongo, Salesforce and other sources into it, and it feeds Tableau, Mixpanel and our internal tools. Queries on big event tables are fast, standard SQL is easy to work with, and I don't need to manage any infrastructure. The MCP connector also lets me query the warehouse straight from Claude, which saves me a lot of time on ad-hoc analysis. Review collected by and hosted on G2.com.

Permissions setup takes time. Every new service account or integration needs the right roles (dataViewer, jobUser) at the project or dataset level, and it's not always clear which one is missing. Cost also needs watching, because a query on a big unpartitioned table can get expensive fast. Some Gemini in BigQuery features were also hard to enable and didn't work right away. Review collected by and hosted on G2.com.

BigQuery is a fantastic data warehouse with nearly unlimited computing power where queries finish within seconds. It has several configuration options for cost management, security setup, and storage options. Review collected by and hosted on G2.com.

Sometimes a unified design within Google is lacking with all of the different products like Knowledge Catalog, BigQuery, Data Fusion, etc. Review collected by and hosted on G2.com.

I use Google Cloud BigQuery to run analytical queries over our database that we can’t do on other persistent stores. I can run really complicated, infrequent queries and get results, and it gives us insights into user behavior from interaction data. Scheduled exports are a really great feature, and I use them to drive daily analytical queries across our huge corpus of data. Setup was pretty easy—we just needed the credentials and were ready to go. Review collected by and hosted on G2.com.

I think the UX could be improved, particularly around AI. It would be great to describe what I’m looking for in natural language and have AI point me to the right table or dataset. Review collected by and hosted on G2.com.