Real-time analytics and AI

Ingest, process, and analyze event streams in real time. Google Cloud's real-time analytics solutions make data more organized, useful, and accessible from the instant it’s generated and brings real-time data to AI models.

The Economic Value of Dataflow: Reduce costs by up to 63% and improve business outcomes

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Benefits

Unify your real-time data

Generate value from your real-time data as part of an AI-ready unified data platform

Real-time data in a unified platform fuels instant insights to empower agile decisions, enhance customer experiences, and enable rapid adaptation to market shifts. Break down data silos for a faster, more responsive organization.

Empower data engineering teams with the flexibility and choice of their preferred open-source software

A fully managed streaming infrastructure solves for scalability, performance tuning, and resource provisioning. Support for SQL, Apache Beam, and Apache Kafka gives you choice and flexibility.

Unify and breakdown silos between operational and analytics systems

Google Cloud's real time capabilities breaks down data silos across analytical and operational systems. Query live operational data with BigQuery and Spanner, push insights to BigTable with reverse ETL, and leverage BigQuery, AlloyDB, and Vertex AI for generative AI and ML

Key features

Real-time made real easy

Adopt simple ingestion for complex events

Ingest and analyze hundreds of millions of events per second from applications or devices virtually anywhere on the globe with Pub/Sub. Directly stream millions of events per second into your data warehouse for SQL-based analysis with BigQuery's streaming API. Or replicate data from relational databases directly into BigQuery on a serverless platform with Datastream.

Unify stream and batch processing without lock-in

Unify streaming and batch data analysis with equal ease and build cohesive data pipelines with Dataflow. Dataflow ensures exactly-once processing, making your streaming pipelines more reliable and consistent for mission-critical applications. Data engineers can reuse code through Dataflow’s open source SDK, Apache Beam, which provides pipeline portability for hybrid or multi-cloud environments.

Keep your current tools while exploring next-generation AI

Bridge, migrate, or extend on-premises Apache Kafka and Apache Spark-based solutions through Confluent Cloud and Managed Service for Apache Spark. Combined with Data Fusion’s GUI, data analysts and engineers can build streaming pipelines in a few clicks. Embed Google’s Vertex AI Workbench solution in your streaming analytics pipeline for real-time personalization, anomaly detection, and predictive maintenance scenarios.

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