Google Cloud BigQuery Reviews & Product Details

its been a long way since, i am using GCP platform, and bigQuery too , i am using BigQuery for data warehousing and ETL. and its amazing and easy to use, i really like its speed, scalability and simplicity. it handles terabyte of data very smoothly. querying is amazing, even for complex joins across multiple large tables.. i also like how easily it integrates with tools like Dataflow. cloud storage and looker studio, i have use it with tableau also. partitioning and clustering features help a lot of optimizing storage and cost. The security and access management through IAM is also useful and easy to handle. Review collected by and hosted on G2.com.

well, i dont have any complaints regarding it, but they could improve query history and job monitoring interface. The UI is clean but can lag a bit when handling too many project.. but apart from that it works reliably. Review collected by and hosted on G2.com.

i am using GCP from last 2 years, and using Bigquery from last 1 year, and really its amazing, how easy it is to use, i like how it makes easy to handle huge datasets and create ML models ,The integration with BigQuery ML is one my favorite feature. i can build and train ML models using only SQL, it support many models types like linear regression, logistic regression, K-means and even TensorFlow models. the performance is very good. even on terabytes of data, it runs fast and stable, the connection with vertex AI and Google cloud storage also helps to move data and models easily. Review collected by and hosted on G2.com.

there is no such major issue with it but debugging model errors or query failure can be a tricky since logs are not always clear, that the only issue otherwise its very powerful and easy to implement. Review collected by and hosted on G2.com.

What I like best about Google Cloud BigQuery is its fully serverless architecture, which removes the need for infrastructure management and capacity planning. It allows us to run large-scale analytical queries on massive datasets without worrying about cluster sizing or performance tuning.

Additionally, BigQuery delivers fast performance and high scalability, even for complex queries, and integrates seamlessly with the broader Google Cloud ecosystem. Features like built-in BigQuery ML, easy data ingestion, and strong integration with tools such as Dataflow and Looker make it highly effective for end-to-end analytics while keeping operational effort minimal. Review collected by and hosted on G2.com.

What I dislike about Google Cloud BigQuery is mainly related to cost control and predictability. Since pricing is based on data scanned per query, it is easy for costs to increase unexpectedly if queries are not well optimized or if users are not careful with large table scans.

Another limitation is less control over execution behavior compared to warehouse-based systems. Because it is fully serverless, there is limited visibility into low-level query execution and fewer tuning options, which can make deep performance debugging more challenging.

Additionally, for teams working across multiple clouds, platform dependency on GCP can be a drawback, as BigQuery is tightly integrated with the Google Cloud ecosystem. Review collected by and hosted on G2.com.

i am using GCP as my primary cloud platform in my workflow and BigQuery is my fav and most used data warehouse, i use it for ETL and Data visualization, its very useful to handle large datasets effortless. the query speed is excellent even with terabytes of data. i also like how easily it integrate with other Google cloud tools like Dataflow, Pub/Sub and looker . writing SQL queries and scheduling jobs in BigQuery feels very efficient and performance tuning features saves a lot of time. Review collected by and hosted on G2.com.

i dont think so there is any problem or a thing to dislike in it, yeah the costing is lil bit high as compared to other Cloud platform but its very powerful and easy to use. also they provide good customer support , and its google so the community is very strong. its very easy to use with Google environment. Review collected by and hosted on G2.com.

I greatly appreciate Google Cloud BigQuery's ability to analyze large datasets without worrying about server size, which simplifies the management of big data. The fast performance of Google Cloud BigQuery saves me from wasting time on slow processing of large datasets, making my work much more efficient. I particularly value its seamless scalability; it scales up and down effortlessly, so I don't have to constantly think about server management. I enjoy how smoothly it integrates with other Google tools, which facilitates the easy movement of data across various platforms and enhances my overall workflow. The ease of setup due to the familiar Google environment is another aspect I find very convenient, making the initial implementation smooth and straightforward. Overall, these features make Google Cloud BigQuery a powerful and user-friendly tool for handling big data efficiently. The customer support is easy to reach, and that increases use frequency. Review collected by and hosted on G2.com.

Sometimes the UI gets chunky and it's difficult to predict prices. The user interface could be cleaner, and price prediction could be improved. Review collected by and hosted on G2.com.

BigQuery is the my favorite tool for ETL. as a SQL developer, i really like how it allows me to work with very large datasets using standard SQL. the query execution speed is excellent, even when dealing with billions of records. The Ui is so clean and i can easily connect it with BI tools like Tableau, Looker studio ,Power BI and other tools to visualize results. I mean its really very powerful, and anyone can use and implement it very easily. Review collected by and hosted on G2.com.

its very powerful but some advance SQL functions work slightly differently in BigQuery compared to traditional databases like MySQL or PostgreSQL so it takes a little time to get used to. Review collected by and hosted on G2.com.

hello, i am an AI Engineer, and i have been using GCP from my college time, and BigQuery is one of my fav tool, i really like how simple and easy to use it its. i mostly work on streaming data so scalability is very important, and it handles large scale data for model training and analytics so easily. the speed is very excellent. The the integration of BigQuery ML is one of my fav part because it allows me to train, evaluate and deploy machine learning models using SQL. so it saves lot of time. also the seamless connection with Vertex AI and cloud storage also makes data preparation for AI projects very smooth. i really enjoying using it in my daily workflow. Review collected by and hosted on G2.com.

I see that, advance model tunning options in BigQuery ML are limited as compared to TensorFlow or PyTorch, but overall its best. Review collected by and hosted on G2.com.

the 1st thing i like is that its Google, and second thing is i really appreciate how powerful and effortless it is. The traditional SQL queries run slower on Big Datasets. but on BigQuery, queries run so fast on billions of rows without any extra servers or infrastructures . it very scalable for real time data too. also the BigQuery ML is very useful to create ML models on prediction and the data visualization is easy with Looker. and the integration with other GCP services like Cloud storage, dataflow and pub/sub makes my ETL and analytics pipelines smooth Review collected by and hosted on G2.com.

i dont face any kind of issues to dislike it. i mean its very good and powerful platform. yeah i heard that it expensive but also it provides best service so its worth it. Review collected by and hosted on G2.com.

I am a Junior Data analyst, and i am using Google cloud from last 3 years, and BigQuery is one of my fav tool, i really like how simple it is, it handle and query large datasets. even i don't know advance SQL, the interface is very user friendly and easy to learn. The speed is amazing, i can run complex queries on millions of rows and it gives results in seconds. also its integration is awesome, it integrates with google sheets and looker studio for dashboarding, and its Google, so the Google environment works smoothly with each Google software. Review collected by and hosted on G2.com.

before using it in my company, i have used it for personal use also, for my projects , so i have faced that the billing cost is very high, many time , the charges were cut from my bank account. Review collected by and hosted on G2.com.

I have been using BigQuery for handling and analyzing massive datasets and the experience has been excellent, the best part i like is how quickly it processes complex queries , even when with billions of rows. it feels like you dont have to worry about scaling just write SQL and get results fast. I like most is seamless integration with other Google cloud tools like cloud storage and data studio. Review collected by and hosted on G2.com.

the pricing is higher , its kind of tricky, specially for teams not used to pay per query system. if queries are not optimized cost can add up also debugging long queries sometimes feels harder compared to traditional databases. Review collected by and hosted on G2.com.