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Support for pipe syntax in GoogleSQL brings the elegance of piped data flow to SQL queries in BigQuery and Cloud Logging.

From ancient Greek myths of talking statues to the modern-day Alexa and Siri, the concept of machines capable of understanding and responding to human language has captivated us for centuries. In recent years, this concept has evolved into AI chatbots, highly sophisticated tools that can read our queries and perform tasks ranging from customer service to automated alerts.

BigQuery history-based optimizations learn from similar queries to identify and apply additional improvements to the query execution.

Bigtable provides the query latency that real-time systems need when using data from BigQuery via the EXPORT DATA to Bigtable (reverse ETL) function.

The BigQuery tables for Apache Iceberg storage engine offers autonomous storage optimizations, clustering, and high-throughput streaming ingestion.

BigQuery external datasets for Spanner let you browse, explore and query Spanner tables as if they were native BigQuery tables.

Learn about an architecture built on BigQuery Omni that reduces the overall cost of log analytics by 10x as compared to a traditional approach.

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

As a serverless, managed service, the new BigQuery Engine for Apache Flink helps organizations bring real-time streaming data to Google AI services.