Business/Customer Intelligence & Data Science

Striim, Inc. announces Striim for BigQuery

No-code managed service Striim for BigQuery automates building and managing data pipelines from enterprise-grade databases into Google BigQuery

Today, Striim, Inc. announced Striim for BigQuery, the first streaming SaaS solution that uses change data capture (CDC) technologies to integrate and replicate data from enterprise-grade databases such as Oracle, MS-SQL, PostgreSQL, MySQL and others to Google Cloud BigQuery enterprise data warehouse. Customers can quickly build a new data pipeline to stream transactional data from hundreds and thousands of tables to BigQuery with sub-second end-to-end latencies to enable real-time analytics and address time-sensitive operational issues. To get started with Striim for BigQuery, visit

“Enterprises are increasingly seeking solutions that help bring critical data stored in databases into Google BigQuery with speed and reliability,” said Sudhir Hasbe, Sr. Director, Product Management, Google Cloud. “With the Striim for BigQuery solution, customers can more easily integrate their data into Google BigQuery and begin analyzing and driving business value with data more quickly throughout their organizations.”

Organizations replicate data from multiple databases to cloud data warehouses, data lakes, and data lakehouses to enable their data science and analytics teams to optimize their decision-making and business workflows. Legacy data warehouses are not easily scalable or high-performant enough to deliver real-time analysis capabilities, while cloud-based data ingestion platforms can require significant effort to set up.

Striim for BigQuery builds on Striim’s award-winning data integration and streaming capabilities to simplify building and operating pipelines to bring real-time streaming data to BigQuery. Using the newly-designed user interface, customers can configure and observe the ongoing and historical health and performance of their data pipelines, reconfigure their data pipelines to add or remove tables on the fly, and easily repair their pipelines in case of failures.

“Fresh data is essential for enterprises to make the right business decisions at the right time,” said Alok Pareek, Executive Vice President of Engineering and Products at Striim. “Our customers are increasingly using BigQuery for their data analytics needs. We have designed Striim for BigQuery for operational ease, simplicity, and resiliency so that our customers can quickly and easily extract business value from their data. We have automated schema management, snapshot, CDC coordination, and failure handling in the data pipelines to deliver a delightful user experience. ”

Striim for BigQuery provides a high level of automation. With a few clicks, customers can set up their data pipelines, and Striim takes care of the rest. Striim uses patented technologies and BigQuery best practices to parallelize writing to BigQuery to maximize pipeline throughput and reduce end-to-end latencies. Striim continuously monitors and reports pipeline health and performance. When it detects tables that cannot be synced to BigQuery, it can automatically quarantine the errant tables and keep the rest of the pipeline operational, thus preventing hours of pipeline downtime. Striim for BigQuery natively stores and reports health performance data so customers can quickly analyze and optimize pipeline performance based on real-time, near-term, and historical data.

Customers can launch Striim for BigQuery from Striim builds and hosts the data pipelines in the customer’s chosen Google Cloud region, thus enabling them to meet their business and regulatory requirements. Striim for BigQuery is designed with standard enterprise-grade security and reliability features, including end-to-end encryption, schema evolution, efficient state management, and automated alerting, monitoring, and notifications.

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