Google Cloud BigQuery Reviews & Product Details

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 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.

UI / UX:

The interface is clean and intuitive, especially when writing and testing queries. Features such as query history, saved queries, and inline validation make it easy to iterate quickly. Even with complex queries, the editor feels smooth and responsive, which helps reduce overall development time.

Integrations:

BigQuery integrates seamlessly with tools like Looker, Data Transfer Service, and other Google Cloud products. This makes it easier to build end-to-end data pipelines without relying heavily on custom integrations. Having a centralized data warehouse that connects effortlessly to reporting tools has also significantly improved data consistency.

Performance:

Performance is one of BigQuery’s biggest strengths. I can run queries on very large datasets and still get results in seconds. This has drastically reduced turnaround time for analysis and reporting, which supports faster decision-making.

Pricing / ROI:

The pay-as-you-go pricing model offers good value, especially since I only pay for the queries I run. Combined with the time saved from not managing infrastructure and the ability to get insights faster, it delivers strong ROI.

Support / Onboarding:

Getting started with BigQuery is relatively straightforward, particularly for users already familiar with SQL. The documentation is solid, and the broader ecosystem makes onboarding easier compared to traditional data warehouses.

AI / Intelligence:

Built-in capabilities like BigQuery ML, along with integrations with AI tools, add extra value by enabling predictive analytics directly within the platform. This reduces the need to move data into external systems and supports more advanced use cases within the same environment.

The resources and documentation are also straightforward and easy to understand. Review collected by and hosted on G2.com.

One ongoing challenge is cost visibility and control. Because pricing is based on the amount of data processed per query, costs can rise unexpectedly when queries aren’t optimized. This means users need to pay close attention to query design and monitor usage carefully.

The UI can also feel somewhat limited for more advanced workflows. It works well for writing queries, but managing complex pipelines or debugging issues may require switching between multiple tools or leaning on external solutions.

Another drawback is the limited flexibility when troubleshooting. If jobs fail or data transfers run into problems, the error messages aren’t always very descriptive, which can make debugging more time-consuming than it needs to be.

Finally, while onboarding is generally smooth, it can still take time to learn best practices such as partitioning, clustering, and cost optimisation—especially for new users. Review collected by and hosted on G2.com.

Easily connects to Google products, such as Sheets, Cloud Storage. Review collected by and hosted on G2.com.

Navigation within Google Cloud is difficult. All the different platforms and solutions are very confusing to navigate for non-technical users Review collected by and hosted on G2.com.