Cloud Bigtable is a highly scalable, fully managed NoSQL database service that offers single-digit millisecond latency and an availability SLA up to 99.999%. It is a good choice for applications that require high throughput and low latency, such as real-time analytics, gaming, and telecommunications.
Cloud Bigtable change streams is a feature that allows you to track changes to your Bigtable data and easily access and integrate this data with other systems. With change streams, you can replicate changes from Bigtable to BigQuery for real-time analytics, trigger downstream application behavior using Pub/Sub (for event-based data pipelines), or capture database changes for multi-cloud scenarios and migrations to Bigtable.
Cloud Bigtable change streams is a powerful tool that can help you unlock new value from your data.
NBCUniversal’s streaming service Peacock uses Bigtable for identity management across their platform. The Bigtable change streams feature helped them simplify and optimize their data pipeline.
“Bigtable change streams was simple to integrate into our existing data pipeline leveraging the dataflow beam connector to alert on changes for downstream processing. This update saved us significant time and processing in our data normalization objectives.” – Baihe Liu, Peacock
Actuating your data changes
Enabling a change stream on your table can easily be done through the Google Cloud console, or via the API, client libraries or declarative infrastructure tools like Terrafom.
Once enabled on a particular table, all data changes to the table will be captured and stored for up to seven days. This is useful for tracking changes to data over time, or for auditing purposes. The retention period can be customized to meet your specific needs. You can build custom processing pipelines using the Bigtable connector for Dataflow. This allows you to process data in Bigtable in a variety of ways, including batch processing, streaming processing, and machine learning. Or, you can have even more flexibility and control by integrating with the Bigtable API directly.
Cloud Bigtable change streams use cases
Change streams can be leveraged for a variety of use cases and business-critical workloads.
Analytics and ML
Collect event data and analyze it in real time. This can be used to track customer behavior to update feature store embeddings for personalization, monitor system performance in IoT services for fault detection or identify security threats, or monitor events to detect fraud.
In the context of BigQuery, change streams can be used to track changes to data over time, identify trends, and generate reports. There are two main ways to send change records to BigQuery: as a set of change logs or mirroring your data on BigQuery for large scale analytics.
Leverage change streams to trigger downstream processing of certain events, for example, in gaming, to keep track of player actions in real time. This can be used to update game state, provide feedback to players, or detect cheating.
Retail customers leverage change streams to monitor catalog changes like pricing or availability to trigger updates and alert customers.
Migration and multi-cloud
Capture Bigtable changes for multicloud or hybrid cloud scenarios. For example, leverage Bigtable HBase replication tooling and change streams to keep your data replicated across clouds or on-premises databases. This topology can also be leveraged for online migrations to Bigtable without disruption to serving activity.
Compliance often refers to meeting the requirements of specific regulations, such as HIPAA or PCI DSS. Retaining the change log can help you to demonstrate compliance by providing a record of all changes that have been made to your data. This can be helpful in the event of an audit or if you need to investigate a security incident.
Change streams is a powerful feature providing additional capability to actuate your data on Bigtable to meet your business requirements and optimize your data pipelines. To get started, check out our documentation for more details on Bigtable change streams, along with these additional resources:
Expanding your Bigtable architecture with change streams
Process a Bigtable change stream tutorial
Bigtable change streams Code samples