BigQuery Reviews

Organizations experienced enhanced ROI with BigQuery through cost savings and performance improvements. They noticed a 27% boost in query performance and a 17% reduction in total expenses. Although training took six months, the benefits became apparent within a year. BigQuery efficiently manages large datasets and offers substantial cost advantages, reportedly achieving around 75% savings compared to other services. It delivers effective tools for data analysis, appealing to entities looking for hassle-free and plug-and-play capabilities.

BigQuery provides flexible and competitive pricing for enterprise users, with a pay-as-you-go model based on data storage and query execution. Users highlight its cost-effectiveness compared to solutions like Snowflake. The first 1 TB per month is free, with additional charges for increased usage. Pricing varies depending on the amount of data processed rather than time spent. Proper planning and optimization can significantly reduce costs, making it an appealing option within Google Cloud Platform.

• "We are above the free threshold, so we are paying around 40 euros per month for BigQuery."
• "The product operates on a pay-for-use model. Costs include storage and query execution, which can accumulate based on data volume and complexity."
• "The platform is inexpensive."

Primary use cases for BigQuery include data storage, querying, and transformation. Organizations leverage BigQuery for data warehousing, analytics, machine learning, real-time data processing, and reporting. It's favored for seamless integration with other Google Cloud services, scalability, and flexibility. Applications span various sectors like banking, marketing, healthcare, and commerce, utilizing BigQuery for diverse tasks such as mobile data processing, customer segmentation, behavioral data analysis, and enterprise data migrations.

BigQuery customer service is generally responsive, with technical support praised for its agility and effectiveness. However, some users encounter delays unless using higher-tier plans. Many rely on documentation and community resources, limiting direct support interaction. Google's overall support receives mixed ratings, with some users finding it good, but room for improvement exists in resource availability. Users mainly address issues internally, and technical challenges are manageable with dedicated investigation.

BigQuery's initial setup is mostly straightforward, often compared to creating a Gmail account. Users appreciate its cloud-based nature, eliminating installation worries. Setting it up can often be completed quickly, taking anywhere from 30 minutes to a couple of days, depending on experience and requirements. It's simple for those familiar with cloud services, though initial integration and data ingestion may require technical skills. Most find setup manageable without needing extensive external help.

BigQuery demonstrates impressive scalability, efficiently handling vast data and complex queries. Many organizations utilize it effortlessly without configuration concerns, benefiting from auto-scaling for dynamic resource management. Although highly scalable, some users note limitations with query limits and performance challenges with massive datasets. The platform’s cloud-based nature allows easy scaling, but the pricing may not suit smaller operations. Most users rate its scalability high, appreciating seamless adaptation to varying workloads and large data volumes.

Users describe BigQuery as a very stable service with high reliability, often rated between seven and ten out of ten for stability. Built-in Google capabilities contribute to commendable performance, handling large datasets without crashing. A few issues like query limitations and regional service delays have been noted, but Google's robust support promptly addresses these concerns. Many believe BigQuery will expand its market presence, given its consistency and data integrity.