BigQuery is your AI-ready data analytics platform

BigQuery gives you the flexibility to use existing open source formats. BigLake, BigQuery's storage engine, provides a unified interface for analytics and AI engines to query multiformat, multicloud, and multimodal data. BigQuery supports Iceberg, Delta, and Hudi along with all processing engines and full capabilities over all of these table formats.

BigQuery Studio is a one-stop shop for all data practitioners. BigQuery Studio has a great SQL editor as well as Python Notebooks. This allows your data teams their choice of SQL, Python, Spark, or natural language. Data teams can maximize productivity by collaborating with the Gemini-powered chat and code assistant within BigQuery.

BigQuery makes it easy for you to manage, discover, and govern data with data governance capabilities built-in to BigQuery. This includes data quality, lineage, and profiling as well as governance rules to manage policies on BigQuery resources.

Ingest, process, and analyze event streams in real time to make data more useful and accessible with BigQuery's real-time capabilities. BigQuery continuous queries provides a real-time processing layer to analyze and transform incoming events in BigQuery. Customers can use Apache Kafka for BigQuery to manage streaming data workloads without the need to worry about version upgrades, rebalancing, monitoring, and other operational headaches.

BigLake unifies data lakes and warehouses under a single management framework, enabling you to analyze, search, secure, govern and share unstructured data. Customers are already analyzing images using a broad range of AI models. BigLake has expanded capabilities to help you easily extract insights from documents and audio files using Vertex AI’s document processing and speech-to-text APIs.

BigQuery vector search is integrated with Vertex AI to enable vector similarity search on your BigQuery data. This functionality can enable use cases like semantic search, similarity detection, and retrieval-augmented generation (RAG) with a LLM. Vector search can enhance the quality of your AI models by improving context understanding, reducing ambiguity, ensuring factual accuracy, and allowing adaptability to different tasks and domains.

BigQuery helps you collaborate and securely exchange data assets at scale. You can create and manage environments for privacy-centric data sharing and analysis with data clean rooms. Data providers can manage subscriptions to data listings and monitor subscriber usage of shared data. You can share data across clouds with BigQuery Omni, and there is support for user defined functions, time travel, and materialized views over linked datasets.

BigQuery Migration Service is a set of free tools to help you migrate to BigQuery. We continue to add new capabilities and now support different sources including Amazon Redshift, Apache HiveQL, Netezza, Teradata, Azure Synapse, Oracle, Presto, Snowflake, SQL Server, and Vertica. Generative AI-enhanced translations optionally aid the query compiler and automatically suggest output options with support for migrations from on-prem and cloud sources.