i am using GCP as main cloud platform, along with Azure, and BigQuery is my favorite data warehousing tool and also for model development. i like it because its fast and stable, and also its scalability is great as compare to other cloud. its been more than 2 years , and still using it for handling huge datasets so easily. and i just love the integration of BigQueryML , i mean its amazing i can build and train simple ML models directly using SQL. it helps me a lot when i want to test quick predictions or run feature analysis without moving data to another platform, i have connected it with Vertex AI and looker and Tableau. to make end to end pipelines. and it really easy to use. Review collected by and hosted on G2.com.

i dont have any complaint about performance issue, but yeah its lil bit costly, if i run multiple experiments or large queries, it can get expensive fast,. but its okay because i am getting fast and large scale ML workflows. Review collected by and hosted on G2.com.

GCP is my primary Cloud platform in my company. And i use BigQuery daily for data warehousing and ETL process. I like it , its really very fast as compare to other cloud , and its easy to use for any datasets. i have queried billions of rows using just SQL . And personally i just love the google environment, like it integrates with Google CLoud , dataflow and google storage, also i have integrated it with Tableau for data visualization. its very smooth, i like how easy it is to load data from different source. Review collected by and hosted on G2.com.

its been a year now , and still i am using it without any issues, like costing okay because its performance is very good, but its not for personal use or small project because its lil bit expensive. Review collected by and hosted on G2.com.

It works similarly to other databases, and it also supports scripting in multiple languages such as shell scripts, SQL, and JavaScript. We used it to build interactive vulnerability data dashboards in Google Looker Studio by extracting data from Axonius into BigQuery and then using BigQuery as the data source. Review collected by and hosted on G2.com.

We’ve scheduled multiple SQL jobs, and when they failed during the daily runs, we wanted to send an email notification. However, we weren’t able to configure the email setup. Review collected by and hosted on G2.com.

I really like Google Cloud BigQuery's interface; it’s very neat and everything looks like it's in one place. I can easily switch between BigQuery, Vertex AI, and other tools I need, making transitions smooth and finding whatever I'm looking for pretty easy. It's very convenient. I also appreciate the advanced SQL features it offers compared to standard SQL. It makes some tasks easier, and I find the estimation of query costs really helpful as it allows me to optimize my queries before running them. Review collected by and hosted on G2.com.

no negative point Review collected by and hosted on G2.com.

well i am using bigquery from last 8 to 9 months , and its amazing, its is extremely fast and efficient when working with too large volume of data, i really appreciate that it support standard SQL, which makes it easy to use without much training , the serverless setup saves a lot of time since we dont need to manage any hardware or performance tuning. it integrate smoothly with other google cloud service, which helps in building complete data pipelines . overall it gives great performance and flexibility for analytical workloads. Review collected by and hosted on G2.com.

well there nothing to dislike in it but sometimes if queries are not properly optimized, better cost alerts and query optimization tips inside the console would make it even better Review collected by and hosted on G2.com.

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.

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.