Continuous, Real-Time Data Movement to Google Cloud
Striim for Google Cloud
Unify your data in Google Cloud with a full suite of real-time data integration solutions. Whether it's automated database migrations to Google Cloud or data integration for BigQuery, Striim will help you get there faster.
Cloud-Hosted, Real-Time Data Integration
Available on the Google Cloud as a PaaS solution, the Striim platform offers non-intrusive, real-time data ingestion from databases, data warehouses, Salesforce, Amazon S3, log files, messaging systems, sensors, Hadoop and NoSQL solutions to Google Cloud with in-flight transformations and enrichments. Striim offers optimized data delivery with sub-second latency to Google BigQuery, Google Cloud Spanner, Google Cloud SQL (for SQL Server, MySQL, PostgreSQL), Google Cloud Pub/Sub, and Google Cloud Storage.
Why Striim For Google Cloud?
Integrate change data from databases, such as Oracle, SQL Server, MySQL, PostgreSQL, HPE NonStop, and AWS RDS, and from data warehouses to Google Cloud with sub-second latency.
Ingest data from in-production sources with negligible impact. Make your operational data available immediately for applications and services on the Google Cloud.
Ease and accelerate development via intuitive, wizards-based development. Write processing using SQL queries and UI-based operators. Get started in minutes.
Striim gives us a single source of truth across domains and speeds our time to market delivering a cohesive experience across different systems
Neel Chinta, IT Manager at Macy's
Why Striim?
Optimized connectors
Over 100 connectors optimized for change
Infinitely scalable
Scale your compute horizontally to meet your data processing needs
SQL-based transformations
Express all business logic on scalable, in-memory SQL queries
Deploy anywhere
On-premise, on any major cloud, or a hybrid topology
High availability
Ensure zero downtime with multi-node failover
Operational analytics
Know and predict what is happening at all times with real-time dashboards, alerts, and machine learning