Google Big Query
BigQuery is Google's fully managed, serverless data warehouse designed for scalable, real-time analytics. Leveraging the power of Google Cloud infrastructure, it enables businesses to run fast SQL queries across large datasets while eliminating the need for complex infrastructure management. With built-in AI and machine learning capabilities, including support for Gemini AI, BigQuery drives intelligent, data-driven decision-making at scale.Google Big Query is already an ISV partner of our Entirely Founding Partner Marmind.
Scalable and Cost-Effective Data AnalysisBigQuery’s serverless architecture removes the burden of infrastructure management, allowing businesses to focus on analytics. With a pay-as-you-go model, users only pay for the storage and compute power they consume, making data analysis more cost-efficient and accessible. |
High-Performance Querying For Massive DatasetsBigQuery is optimized for high-speed queries, processing petabytes of data in minutes. Its columnar storage format and distributed computing architecture enable businesses to analyze massive datasets rapidly, unlocking insights without traditional performance bottlenecks. |
Integrated Machine-Learning and AI FeaturesWith built-in AI and ML functionalities, including support for Gemini AI, BigQuery allows businesses to create and deploy machine learning models directly within SQL workflows. This seamless integration democratizes AI-driven analytics, making predictive insights more accessible without requiring extensive coding expertise. |
Multicloud Analytics and FlexibilityBigQuery provides a flexible, multicloud analytics solution, enabling businesses to analyze data across different cloud providers without the need for data migration. This ensures a unified, real-time view of all business-critical data, regardless of where it resides. |
Stats
8,000+companies rely on BigQuery–trusted by enterprises leveraging machine learning, big data, and AI for advanced analytics. |
12.74%market share in data warehousing – a significant footprint in the global data analytics landscape. |
2000xcost savings on queries – achieving massive efficiency gains by reducing engineering and labor costs in data processing |