BigTable is a fully managed, extremely scalable NoSQL database service designed for real-time analytics on massive datasets. It’s ideal for applications needing low latency, high throughput, and scale—like IoT, finance, and time-series analysis.

Wide-column store

Uses tables comprised of rows and column families; each row is indexed by a string key and can have unlimited columns grouped logically.

Clustered for scalability

Data is split into tablets and distributed across nodes for performance and reliability. Adding nodes increases both storage and query capacity instantly.

High performance

Single-digit millisecond latency for reads/writes, supporting millions of operations per second at scale.

Managed service

Automatic backups, replication, and failover are handled by Google. Built on Colossus file system for durability.

Schema flexibility

Rows can have different columns; schema evolves naturally. Table structure is flexible, enabling diverse use cases.

Security and IAM

Data encrypted at rest and in transit; access controlled using Identity and Access Management (IAM).

How to refer to a table in Bigtable

Reference a table using: instance-id/table-name

Each table belongs to a unique instance, which you create in a GCP project.

Regions in Bigtable

Instances can be regional (single zone) or multi-regional (replicated across zones for high availability). Replication improves resilience and enables disaster recovery.

Schemas in Bigtable

Design schema by specifying row key structure, column families, and data encoding. No enforced schema for columns—add columns dynamically as application requires.

• Row keys should be designed for efficient scans
• Column families defined up front, columns within families can be created as needed

Import data into Bigtable

Data can be imported via Dataflow pipelines, Hadoop tools, or custom applications using Bigtable’s client libraries (Java, Go, Python, C++).

Bigtable vs. traditional SQL databases

Bigtable is not relational: it lacks joins and multi-row transactions, but excels at massive throughput and horizontal scalability.

Bigtable integration

Compatible with HBase API, and integrates with Hadoop, Spark, Dataflow, and more. Works with monitoring and analytics tools in GCP and open-source ecosystems.

What are native tables?

Native Bigtable tables are stored in Google’s infrastructure, optimized for speed and scale.

Costs for Bigtable

Costs include node hours, storage, and network usage. You pay for the number of provisioned nodes (performance), plus storage (SSD or HDD).

Create an instance and table in Bigtable

You create an instance, then add tables and column families through the GCP Console, CLI, or API.

Sample query on Bigtable data

ReadRows API to scan from rowkey "user1" to "user9"

Monitoring Bigtable

Monitor node performance, tablet distribution, read/write latency, and replication status via GCP Monitoring dashboards.