Google Cloud BigQuery Reviews & Product Details

I use Google Cloud BigQuery for large-scale data analytics and reporting, and I love its speed and scalability, which greatly enhance my data processing tasks. The standout feature for me is its serverless architecture, which makes it incredibly easy to scale up or down as needed, eliminating the complexities of maintaining physical servers or a complex data infrastructure. This ease of scalability allows for seamless and efficient use, ensuring that performance is not compromised even with fluctuating workloads. Additionally, I find the initial setup to be very straightforward, which minimizes the time and effort needed to get started, allowing me to focus on analysis and insights rather than logistical hurdles. Review collected by and hosted on G2.com.

One area which can be improved is cost transparency. Review collected by and hosted on G2.com.

I really like how fast and effortless it feels to work with large datasets. BigQuery lets me run complex queries in seconds without worrying about infrastructure, and that simplicity is what stands out the most for me. Review collected by and hosted on G2.com.

The main downside for me is the cost unpredictability. If you’re not careful with query design or data scanned, the charges can add up quickly. A bit more transparency and guardrails would make it even better. Review collected by and hosted on G2.com.

It is very good platform and is very fast and easy to use and it can solve billions of queries in one go and it is super efficient than other cloud platforms available . it provide sql support and make very easy to use for the studetns. Review collected by and hosted on G2.com.

for big projects it is too powerfull and unnecessary to use , it is quite complex for beginers without cost hanndling knwlodege and queries scanning cost me increase very much. Review collected by and hosted on G2.com.

I really like Google Cloud BigQuery's speed, which allows me to run heavy queries on huge datasets in just a few seconds. This speed is crucial for analyzing large datasets efficiently and provides quick insights, significantly saving my time and effort during analysis. The SQL-based interface enhances usability, making it easy to use even when handling big workloads without hassle. Additionally, the setup process is quite simple, which facilitates a smooth transition to using the platform for data analysis. Review collected by and hosted on G2.com.

Sometimes the cost can hike if queries aren't optimized, which can be a concern. More proactive alerts before running expensive queries would help manage costs better. Review collected by and hosted on G2.com.

I really appreciate Google Cloud BigQuery for its outstanding performance. The system's swift and efficient processing capabilities allow me to handle large datasets seamlessly for data analysis. This aspect significantly boosts my productivity and responsiveness when dealing with data analytics and storage. Additionally, I find the platform's response signals to be remarkably effective, ensuring smooth and coherent data transformations. What truly stands out to me is its reliability, highlighted by virtually zero downtime. This reliability ensures that my analytics operations remain uninterrupted and consistent, which greatly enhances operational efficiency and trust in the system. Review collected by and hosted on G2.com.

I think the platform could be simplified much more. Compared to AWS or Azure, Google Cloud BigQuery feels more complex, and a simplified version would improve usability. Review collected by and hosted on G2.com.

Big query os its sheer speed and scalability. We are dealing with massive datasets, and the ability to run complex queries and get results in seconds is a game changer. The serverless architecture is a huge plus I don't have to worry about managing infrastructure, which frees me up to focus on data analysis. And seamless integration is amazing with Google cloud ecosystem like BigQuery, Cloud Run, Cloud Storage and Tableau. Review collected by and hosted on G2.com.

As we know Google Cloud Big Query is bigger tool than other, almost everything is perfect but some minor issues like pricing calculation is tricky in starting or new commers after hands on e

Practice users an easily handle cost management. Review collected by and hosted on G2.com.

BigQuery is a tool designed for thinking at scale, making it ideal for organizations seeking high performance, scalability, and ease of use without the hassle of DevOps management. As a data warehouse, it genuinely delivers a cloud-native experience. Review collected by and hosted on G2.com.

One thing to be aware of with Google Cloud BigQuery is that costs can rise rapidly if queries are not properly optimized or if you frequently scan large datasets. Real-time streaming inserts also tend to be expensive and may experience slight delays. Furthermore, debugging complex queries can be difficult because there is limited visibility into the execution details. Review collected by and hosted on G2.com.

I love how fast BigQuery is. No matter how big the data is, it usually gets the job done quickly. I’ve used it for marketing and sales reports, and it’s super helpful for pulling insights without waiting forever. I also like that it’s easy to share results with my team, especially with dashboards. It saves time and effort every day. Review collected by and hosted on G2.com.

The only real downside is that you can accidentally spend more money than expected if you don’t know how to write efficient queries. It's not always clear how much your query will cost until after it runs. Also, setting up permissions for different team members can be a little confusing. Review collected by and hosted on G2.com.

What I like most is how easy it is to run queries on massive amounts of data and get results quickly. I don’t have to manage servers or tune performance — BigQuery handles all that in the background. The integration with other Google Cloud tools makes building pipelines and dashboards straightforward, and I can focus on the actual analysis rather than worrying about storage or scaling issues. Review collected by and hosted on G2.com.

The main challenge is cost management. Since pricing depends on the amount of data scanned, a single unoptimized query can get expensive, especially when dealing with very large datasets. There’s also a learning curve for new users to understand query optimization and table partitioning. I wish the console had better built-in tools for monitoring query performance and troubleshooting errors. Review collected by and hosted on G2.com.

What I like best about Google Cloud BigQuery is how easy it makes working with large amount of data. I don't have to worry about servers or setups it just work. I can write simple SQL queries and get fast results even with millions of rows. its also great that i can connect it with Google sheets Looker studio and even use Python when i want to do more. The biggest upside is how much time it saves me. instead of waiting for data to load or worrying performance , i can focus on finding insights and making decisions quickly. Review collected by and hosted on G2.com.

When I dislike about Google Cloud BigQuery is that the pricing can be confusing at first especially for someone new to cloud tools. Since it charges based on the amount of data processed per query. Its easy to go over budget if you are not careful with your queries. also the user interface feels a bit technical. The web UI can be slow or unresponsive at time, there is also a steep learning curve for beginners unfamiliar with its architecture. Review collected by and hosted on G2.com.