Google Cloud BigQuery Reviews & Product Details

I appreciate Google Cloud BigQuery's serverless design, which allows me to analyze large datasets quickly without the burden of managing the underlying infrastructure. The built-in machine learning capabilities are a significant advantage, enabling me to create and predict patterns directly using SQL within the data warehouse, which enhances our data analysis processes. Its ability to handle big datasets swiftly and easily solves the challenge of managing complex data efficiently. I also enjoy its seamless integration with the Google ecosystem, which boosts its scalability and enhances performance. The setup is convenient with no need for physical infrastructure, focusing more on project and access setup, which simplifies the initial configuration phase. Review collected by and hosted on G2.com.

I find the cost of Google Cloud BigQuery to be a significant concern, as it can become quite expensive. Additionally, I encounter limitations with its support for complex transactions, which can be restrictive for more advanced data operations. There's also an issue with data export limitations, which can hinder my ability to move data efficiently. Furthermore, I find the user interface usability lacking, which sometimes complicates the navigation and overall user experience. Review collected by and hosted on G2.com.

I find Google Cloud BigQuery extremely advantageous for handling our organization's big data storage and data warehouse needs due to its remarkable speed and efficiency in querying large volumes of data. This efficiency significantly enhances our ability to process extensive datasets swiftly. I also appreciate the data partitioning and storage capabilities, along with its ability to keep track of data history, which are incredibly beneficial. Additionally, the capacity to build views and tables over our data paired with the integration options such as enabling Looker Studio and other dashboards allows us to gain valuable insights from our data seamlessly. Moreover, the support provided by the Google team is exemplary, consistently delivering prompt and effective resolutions to any issues we encounter. Review collected by and hosted on G2.com.

I find it expensive to perform simple queries like 'SELECT *' on very large tables in Google Cloud BigQuery. If there were a way to reduce these costs, it would be beneficial. Review collected by and hosted on G2.com.

As a Data engineer , i am working with massive datasets on a daily basis, BigQuery has completely helped me to make ETL easier. I like best is its serverless platform and blazing fast query performance . also i just love the seamless integration with Google Cloud ecosystem like BigQuery and cloud storage integration and also Tableau. It allows me to move data smoothly between systems and build automated pipelines without any issues. Review collected by and hosted on G2.com.

the pricing visibility for very large query runs sometimes heavy queries can become expensive if not optimized properly, better query cost estimation tools would make it easier to plan workload. Review collected by and hosted on G2.com.

BigQuery has become a core part of my daily workflows as a Senior Data specialist. What stands out the most is its ability to handle massive datasets easily. the architecture without any server removes the hassle of infra management. I like seamless integration with other Google Cloud services. SQL based interface makes it accessible for both analyst and data scientist,and ability to run ML models directly in BigQuery has been a game changer for advanced analytics. Review collected by and hosted on G2.com.

cost optimization can sometimes be tricky, especially for frequent queries on very large tables. proper partitioning and clustering are required to keep costs under control. Review collected by and hosted on G2.com.

I like that Google BigQuery makes it effortless to analyze massive datasets at high speed without worrying about infrastructure. The serverless architecture scales automatically, and I can query billions of rows in seconds using standard SQL. Integration with Google Cloud services, built-in machine learning, and seamless connection to tools like Looker Studio make it very powerful for both data engineers and analysts. Review collected by and hosted on G2.com.

The main challenge with BigQuery is cost management—queries that aren’t optimized can become expensive quickly. Some SQL functions behave differently compared to traditional databases, so there’s a bit of a learning curve. Also, transactional operations and frequent row-level updates are limited, which makes it less suitable for OLTP-type workloads. Review collected by and hosted on G2.com.

As a Data analyst, i use BigQuery almost daily to query, clean and analyze large datasets. I really like how easy it is to connect BigQuery with visualization tools like Looker studio and Tableau. The integration with Google sheets is also very handy for lightweight reporting when stakeholders prefer a simple spreadsheet format. The UI is very friendly. and the ability to write queries directly in the browser is convenient for analysis. its very easy to implementation. Review collected by and hosted on G2.com.

The main challenge is cost management. Since BigQuery charges based on data processed, exploratory analysis can become expensive if queries are not optimized. Review collected by and hosted on G2.com.

BigQuery is fast, serverless, and lets me focus on clean SQL instead of worrying about servers or infrastructure, which makes data analysis feel smooth and efficient Review collected by and hosted on G2.com.

Pricing is confusing, setup (project + billing) feels complex, and the UI can be cluttered for learners who just want a simple, safe place to practice queries Review collected by and hosted on G2.com.

I value how BigQuery combines speed with ease of use. Setting it up is not overwhelming or complicated, and it processes queries quickly, even when dealing with substantial datasets, without requiring a lot of fine-tuning. Another advantage is how it simplifies my workflows by integrating smoothly with other Google Cloud services. Review collected by and hosted on G2.com.

One downside I’ve observed is that costs can escalate quickly if I’m not attentive, as charges depend on the volume of data queried. Executing large or complex queries can significantly increase expenses. Since I don’t use BigQuery daily, I occasionally need to reacquaint myself with certain features, and troubleshooting long SQL jobs can be challenging. While customer support is helpful, response times can sometimes be slow. Review collected by and hosted on G2.com.

I find Google Cloud BigQuery incredibly powerful for data analysis and dashboard building, particularly because I don't have to worry about managing servers or infrastructure. Its performance in handling large datasets is impressive, especially with how quickly it runs SQL queries on millions of rows, saving me a lot of time during analysis and reporting. What I like the most is its serverless nature, letting me focus on analysis rather than infrastructure; there’s no need to provision machines or handle performance tuning, as BigQuery scales automatically to accommodate large datasets. Additionally, BigQuery integrates exceptionally well with tools like Looker Studio, Google Data Studio, and external BI tools such as Power BI and Tableau, making dashboard creation and report automation smooth. The initial setup experience was straightforward since it is fully serverless, removing concerns about hardware provisioning, cluster configuration, or node management. I would also commend it for its excellent query performance at scale, which further enhances its utility in my workflow. Review collected by and hosted on G2.com.

While Google Cloud BigQuery is powerful, there are a few areas where I feel it could improve. Query costs can be hard to predict because BigQuery charges based on data scanned. Sometimes even a simple mistake, like selecting * on a large table, can result in unexpectedly high costs. Cost control measures exist, but more granular real-time cost visibility during query development would be helpful. I believe that real-time cost simulation before execution could enhance this experience by providing a live cost estimate as queries are being developed. Review collected by and hosted on G2.com.

I appreciate Google Cloud BigQuery's capacity for handling large-scale data analysis and its ability to run complex SQL queries efficiently, generating insights in real time. The serverless design eliminates the need for managing complex infrastructures, which lets me focus more on data extraction rather than hardware maintenance. Its scalability and speed are standout features, processing huge datasets within seconds and optimizing performance automatically without my intervention. Additionally, the seamless integration with tools like Looker, Data Studio, Google Sheets, and Cloud Storage makes it an ideal tool for comprehensive data analytics and business intelligence, streamlining from data ingestion to reporting. The platform’s ease of use, due to its serverless architecture, contributes to a straightforward and efficient initial setup process. The documentation is clear, making the onboarding and integration with other Google tools smooth for my team, and the ecosystem itself proves to be one of its most considerable advantages. Transitioning from an on-premise SQL data warehouse, which had limitations on scalability and performance, to Google Cloud BigQuery drastically improved our data management and query execution speed—all without the burden of infrastructure maintenance. Review collected by and hosted on G2.com.

I find cost management tricky when running frequent or complex queries on large datasets in Google Cloud BigQuery. The service lacks transparent cost estimation tools, which makes budgeting difficult. Additionally, the UI could benefit from enhanced features for query performance tuning. Another area for improvement is the data ingestion process from non-Google sources, which could be simplified with more native connectors. Review collected by and hosted on G2.com.