Ingest, process, and analyze event streams in real time
Stream analytics from Google Cloud makes data more organized, useful, and accessible from the instant it’s generated. Built on the autoscaling infrastructure of Pub/Sub, Dataflow, and BigQuery, our streaming solution provisions the resources you need to ingest, process, and analyze fluctuating volumes of real-time data for real-time business insights. This abstracted provisioning reduces complexity and makes stream analytics accessible to both data analysts and data engineers.
Scale up infrastructure and scale down headaches
Google Cloud’s streaming infrastructure auto-scales to match your data analysis needs. No need to overprovision or overpay for unused resources; Google Cloud handles challenges like variable data volumes, performance tuning, and resource provisioning.
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. Or directly stream millions of events per second into your data warehouse for SQL-based analysis with BigQuery’s streaming API.
Unify stream and batch processing without lock-in
Unify streaming or batch data analysis with equal ease and build cohesive data pipelines with Dataflow. Data engineers can reuse code through Dataflow’s open-source SDK, Apache Beam, which provides pipeline portability for hybrid or multi-cloud environments. Dataflow ensures exactly-once processing, making your streaming pipelines more reliable and consistent for mission-critical applications.
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 Dataproc. Combined with Data Fusion’s GUI, data analysts and engineers can build streaming pipelines in a few clicks. Embed Google’s advanced ML and AI solutions in your stream analytics pipeline for real-time personalization, anomaly detection, and predictive maintenance scenarios.
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Built atop the open source Apache Beam SDK for transforming and enriching ingested data in streaming and batch modes with equal reliability and expressiveness.