What is Cloud Bigtable?
Cloud Bigtable is a fully managed NoSQL database from Google Cloud optimized for analytical and operational workloads with high throughput and low latency. It is the same technology that Google uses internally for services like Search, Maps, and Gmail.
Core Features
- Scaling to petabytes with single-digit millisecond latency
- HBase-compatible API for easy migration
- Seamless integration with Apache Spark, Hadoop, and Dataflow
- Automatic replication across regions for high availability
- Autoscaling based on CPU utilization
Typical Use Cases
Time Series Data: Storage and analysis of IoT sensor data, metrics, or financial market data with fast access to historical ranges.
Personalization: Real-time recommendation systems for e-commerce or media with millions of user profiles and interactions.
AdTech: Storage of bid requests and impression data for real-time bidding systems with extreme throughput.
Benefits
- Linear scaling without performance loss
- Native integration with BigQuery for analytics
- No maintenance windows or upgrades required
- Consistent performance at any scale
Integration with innFactory
As a Google Cloud partner, innFactory supports you with Cloud Bigtable: architecture, migration, operations, and cost optimization.
Available Tiers & Options
Standard
- Lower costs
- Good for development
- Lower SLA
Production
- 99.99% SLA
- Replication
- Auto-failover
- Higher costs
Typical Use Cases
Technical Specifications
Frequently Asked Questions
What is Cloud Bigtable?
Cloud Bigtable is a fully managed, scalable NoSQL wide-column database for workloads with high throughput and low latency.
How does Bigtable differ from Firestore?
Bigtable is optimized for analytical workloads with petabytes of data. Firestore is better suited for mobile/web apps with more complex queries.
What latency can I expect?
Bigtable delivers single-digit millisecond latency for single row lookups with correct schema design and hotspot avoidance.
How does scaling work?
Bigtable scales horizontally by adding nodes. Performance increases linearly with the number of nodes without application changes.
