- Compression and Garbage Collection:
- Cloud Bigtable supports Snappy, LZO, or GZ compression for column families, which can help reduce storage costs and improve query performance.
- Configure garbage collection policies to automatically remove old or unused data from column families, optimizing storage usage and costs.
- Instance Types and Storage Options:
- Choose between two instance types: production and development. Production instances offer higher performance and availability, while development instances are designed for low-cost testing and development environments.
- Select either SSD or HDD storage based on your performance and cost requirements. SSD provides lower latency and higher throughput, while HDD offers lower costs for large-scale data storage.
- Replication and Backups:
- Configure regional or multi-regional replication to ensure high availability and fault tolerance for your Cloud Bigtable data.
- Create backups of your Cloud Bigtable tables to protect against data loss or corruption, and restore them when necessary.
- Resizing Cloud Bigtable Clusters:
- Monitor your Cloud Bigtable cluster’s performance and resource usage, adjusting the number of nodes as needed to handle changing workloads.
- Use the Cloud Console, gcloud CLI, or API to add or remove nodes, ensuring a smooth scaling process.
- Query Optimization:
- Design your queries to minimize the amount of data that needs to be read, which can help improve performance and reduce costs.
- Use filters and row key range scans to target specific data, and avoid full table scans whenever possible.
- Batch and Bulk Operations:
- Use batch operations to efficiently read or write multiple rows in a single request.
- For large-scale data ingestion or modification tasks, consider using the Cloud Bigtable Dataflow connector or bulk import tools like
cbtorbigtable-beam-import.
- Monitoring with OpenCensus and OpenTelemetry:
- Integrate Cloud Bigtable with OpenCensus and OpenTelemetry to collect and analyze application-level metrics and traces, helping you understand and optimize your application’s performance.
- Migrating Data to/from Cloud Bigtable:
- Use the Cloud Bigtable Dataflow connector,
cbt, or custom scripts to migrate data between Cloud Bigtable and other datastores like HBase or Cassandra. - Perform data transformations and validation during migration, as needed, to ensure data consistency and compatibility.
- Cloud Bigtable Emulator:
