PALO ALTO, CA – April 2, 2019 – Striim®, provider of an enterprise-grade platform for streaming data integration, expanded its cloud adoption solution portfolio by announcing a platform as a service (PaaS) solution for real-time data movement to Google Cloud Spanner, available in the Google Cloud Platform (GCP) marketplace. Striim’s Real-Time Data Integration to Cloud Spanner offers online data migration and replication with guaranteed delivery and exactly once processing, as well as ongoing real-time data loading, all through comprehensive streaming data integration capabilities.
With Striim, Cloud Spanner users can quickly build highly reliable, scalable, and performant real-time data pipelines from on-premises and other cloud environments. Using non-intrusive, real-time change data capture (CDC), Striim continuously replicates transactions in other relational databases to Cloud Spanner with no performance impact or operations interruption.
Cloud Spanner users require streamlined, low-risk database migration to support enterprise grade, mission-critical applications. Striim’s real-time data migration capabilities enable Cloud Spanner customers to move data securely from existing on-premises or cloud-based relational databases (such as Oracle, SQL Server, HPE NonStop, MySQL, PostgreSQL) without database downtime or data loss.
“Google’s Spanner service offers global consistency and ACID transactions at scale. To migrate real-world production workloads from on-premises databases to Google Cloud Spanner, Striim’s built-in fault tolerance, scale-out architecture, exactly-once processing, and support for out-of-the-box connectors make it simple for enterprises to migrate data without incurring downtime or requiring extra development,” said Alok Pareek, Co-Founder and EVP of Products at Striim. “Striim enables businesses to use real-time, production data from critical transactional systems to Cloud Spanner, and easily move high-value workloads to GCP.”
Striim’s real-time data pipelines non-intrusively and continuously ingest high-volume, high-velocity data from on-prem and cloud-hosted data sources – including databases via CDC, log files, Kafka, sensors, Hadoop and NoSQL systems – and deliver it into Google Cloud Spanner.
Striim also performs data processing – such as filtering, aggregations, transformations, masking, and enrichment – in real time, as the data is streaming, to deliver highly consumable data to Cloud Spanner.
Striim’s streaming data pipelines can ingest data from a number of data sources, including:
- Database systems (ie, Oracle, SQL Server, MongoDB, PostgreSQL, MySQL, and HPE NonStop) using sophisticated non-intrusive Change Data Capture (CDC) technology
- Data warehouses (ie, Oracle Exadata, Teradata, and Amazon Redshift)
- Messaging Systems (ie, Kafka, JMS)
- Applications (ie, Salesforce), logs generated by applications, networks, and security systems
- Data generated by IoT systems (ie, MQTT, OPC-UA)
For ease of use, Striim offers an intuitive template-based user interface and SQL-based queries to streamline deployment of data pipelines on Google Cloud Platform.
To learn more about Striim’s PaaS offering for Google Cloud Spanner, please visit our Cloud Spanner product page, read the related blog post, or provision Striim for Real-Time Data Integration to Cloud Spanner in the Google Cloud Marketplace.
The Striim®platform is an enterprise-grade streaming data integration solution for moving data in real time to the cloud. Striim makes it easy to continuously ingest and process high volumes of streaming data from diverse sources (both on-premises or in the cloud) to support hybrid cloud infrastructure, as well as Kafka, Hadoop, and NoSQL integration. Striim can collect data from enterprise databases (using non-intrusive change data capture), log files, messaging systems, and sensors in real time, and deliver to virtually any target on-premises or in the cloud with sub-second latency.For more information, visit www.striim.com, read our blog at www.striim.com/blog, follow @striimteam, or download the Striim platform.