What I like best about BigQuery is its ability to handle massive datasets with incredible speed, without worrying about infrastructure. Its serverless, fully managed architecture allows me to focus on analysis and deriving insights, and its integration with other Google Cloud tools makes building dashboards and pipelines seamless Review collected by and hosted on G2.com.

BigQuery is powerful, but query costs can grow if datasets are very large and queries aren’t optimized. I usually work around this by using partitioned tables and caching results. Also, while it’s great for analytics, very complex data transformations often need additional ETL tools—but that’s manageable with the right approach Review collected by and hosted on G2.com.

Storing dataHonestly, the absolute best part is how it instantly turbocharges my AppSheet apps.

When I had to handle a massive 2-lakh row upload, BigQuery handled it effortlessly.

I also love shifting my clunky Apps Script logic into secure BigQuery Stored Procedures.

It keeps the heavy data-manipulation lifting on the database side exactly where it belongs.

Plus, the built-in recovery tools saved me from a total panic attack when I dropped a table!

It just takes all the stress out of managing huge datasets and keeps things running fast. Review collected by and hosted on G2.com.

If I had to pick what frustrates me, it's definitely the strict schema management.

Changing simple things like column data types or the order of columns isn't always as straightforward as it should be.

Trying to perfectly match AppSheet's Duration type to BigQuery gave me a real headache at first.

I also spent way too much time troubleshooting those annoying date and time formatting errors!

It’s incredibly powerful, but sometimes you just want to make quick data tweaks without jumping through hoops. Review collected by and hosted on G2.com.

I like the policy tags on the column level and the structure of Google Cloud BigQuery. Having datasets with tables and views inside them offers a better structure for managing my data. This setup makes data easy to use and helps differentiate between different data types while keeping everything organized. Policy tags are great because they allow correct data distribution to the right people without needing to create separate tables. Integrating Dataform is also easier with this structured approach. Review collected by and hosted on G2.com.

I find that row filtering could be improved to allow using structured columns from a reference table to apply row filtering, which isn't possible currently and made us create expensive workarounds. There are some performance hiccups here and there, and the GCP BigQuery UI can sometimes be overwhelming, with too many things popping up on the screen. Using BigQuery libraries, especially the BigQuery API for Java, was slightly difficult to understand at first, so perhaps a bit better documentation could help, especially around authorization. Also, the initial setup was difficult to understand at first without previous knowledge. Review collected by and hosted on G2.com.

Very easy to use and implement due to its serverless architecture. It provides many built-in features for large-scale analytics, integrates well with other services in Google Cloud, and is reliable for frequent data analysis workloads. Review collected by and hosted on G2.com.

Query costs can be difficult to predict with frequent use, and some advanced integrations or optimizations require additional services within Google Cloud. Customer support and troubleshooting can also depend on the selected support tier. Review collected by and hosted on G2.com.

I like that Google Cloud BigQuery can handle big tables easily, and I can integrate it with other Google products like GA4 or Looker Dashboard. Fetching and processing traffic data from Google Analytics was super easy for me. Review collected by and hosted on G2.com.

Although I know the product is technical, it could have an easier UI so that it would be much easier for beginners or people with low tech expertise. There could have been several improvements like a tool tip explaining what each button is used for, some knowledge base, or an AI bot to help people out. Review collected by and hosted on G2.com.

the thing i like most is powerful, reliable serverless architecture. my job is to build data pipelines, it lets me completely forget about cluster sizing, scaling up for peak loads, and patching servers, i just point my ETL tools like dbt at BigQuery and the query engine handles multi terabyte transformation instantly using parallel processing. the integration with the whole GCP ecosystem cloud storage for storage and airflow for orchestration is seamless, making it easy to build robust , automated pipelines, its a total game-changer for efficiency. Review collected by and hosted on G2.com.

the bill can spike dramatically, very quickly , we had to spend a significant amount of time setting up internal governance, strict user quotas and mandatory partitioning polices to keep the budget under control. Review collected by and hosted on G2.com.

Data in BigQuery is stored in structured tables and thus it helps me to analyze the large chunk of data very easily. We can also use standard SQL commands enabling fast, scalable and efficient data analysis. It is much economical as you only need to pay for the service you use. Review collected by and hosted on G2.com.

BigQuery is good for handling large amount of data but a simple query also might takes a few seconds to run. Review collected by and hosted on G2.com.

Google Cloud BigQuery is the only platform that comes to my mind when it comes to handling large amount of data. The platform is really intuitive and it comes built-in SQL Query tool, to query my data. Review collected by and hosted on G2.com.

The platform can be overwhelming for beginners, but once they get familiarised it is really useful Review collected by and hosted on G2.com.

well, the main thing that i like is its Google, its customer services are top notch, whenever we face any issues, they resolve it asap, i am using GCP from last 4 years, and each service is amazing, BigQuery is my fav data warehousing tool because it has good speed and scalability, i work with it daily to handle huge datasets, and it give me best performance, its other service are so easy to use that i can integrate and implement my workflow easily,,, the SQL interface is very comfortable and features like partitioning and clustering make queries faster with less cost, i have integrated it with tableau and cloud storage. Review collected by and hosted on G2.com.

personally, i just love it , there are no such things to dislike it, yeah it works slowly sometimes , but its negotiable, i dont have any complaints in it. Review collected by and hosted on G2.com.

I like using Google Cloud BigQuery because it eliminates the complete infrastructure step, which is awesome. The easy-to-use interface is a great option from creating to testing. I appreciate the fast performance and the ability to integrate with other tools, like connecting with Google Looker Studio for visualization. It just makes life easier. The initial setup was very easy, and it provides a smooth analysis process with less setup. No infrastructure setup, easy to understand, and a great user interface are significant positives for me. Review collected by and hosted on G2.com.

Maybe the pricing could be a bit better. Review collected by and hosted on G2.com.