Learn how Bitly migrated 80 billion rows of link data to Cloud Bigtable in just six days. Read the blog
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Cloud Bigtable

HBase-compatible, enterprise-grade NoSQL database service with single-digit millisecond latency, limitless scale, and 99.999% availability for large analytical and operational workloads.

New customers get $300 in free credits to spend on Bigtable.

  • Build responsive applications with consistent, single-digit millisecond latency

  • Seamlessly scale to match your storage and throughput needs; no downtime during reconfiguration

  • Easily migrate from Apache HBase to Bigtable with no-downtime, live migrations

  • Ideal for use cases such as personalization, fraud detection, real-time analytics, and IoT

  • Ensure high availability with multi-primary replication in up to 8 regions


Fast and performant

Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics.

Seamless scaling and replication

Start with a single node per cluster, and scale to hundreds of nodes dynamically supporting peak demand at low latency. Replication also adds high availability and workload isolation for live serving apps.

Open and integrated

Easily connect to the open source ecosystem with the Apache HBase API. Build data-driven applications faster with seamless integrations with Hadoop, Dataflow, Dataproc, and BigQuery.

Key features

Key features

High throughput and low latency at any scale

Bigtable is a key-value and wide-column store, ideal for fast access to very large amounts of structured, semi-structured, or unstructured data with high read and write throughput. Bigtable powers many core Google services such as YouTube, Google Analytics, Search, Ads, Drive, and Maps.

Cluster resizing without downtime

Scale seamlessly from thousands to millions of reads/writes per second. Bigtable throughput can be dynamically adjusted by adding or removing cluster nodes—all without any downtime. Bigtable can also autoscale your cluster based on changes in demand so that you can maintain great performance in the most cost-effective way.

Flexible, automated replication to optimize any workload

Write data once and automatically replicate where needed with eventual consistency—giving you control for high availability and isolation of read and write workloads. No manual steps needed to ensure consistency, repair data, or synchronize writes and deletes. Benefit from a high availability SLA of 99.999% for instances with multi-cluster routing across 3 or more regions (99.9% for single-cluster instances).

Easy migrations from Apache HBase and Cassandra to Bigtable

Live migrations enable faster and simpler migrations from HBase to Bigtable by ensuring accurate data migration, reducing migration effort, and providing a better overall developer experience. HBase Bigtable Replication Library allows for no-downtime live migrations, Import Tool easily loads HBase snapshots into Bigtable, and Validation Tool ensures accurate data migration. Dataflow templates simplify migrations from Cassandra to Bigtable. 

Enterprise-grade security and controls

Customer-managed encryption keys (CMEK) with External Key Manager support, IAM integration for access and controls, support for VPC-SC, and comprehensive audit logging help ensure your data is protected and complies with regulations.

Logo for Quantifi Solutions

"With Google Cloud, it’s easier to synthesize large amounts of unstructured data and define complex network efforts. And with Dow Jones DNA fueling our Knowledge Graph, you can quickly leverage decades of knowledge in a way that makes connections more accurate. These business insights can unlock new revenue opportunities and reduce risks and costs for our customers."

Asif Hasan, Co-founder & President, Quantiphi

Learn more



Codelab: Introduction to Cloud Bigtable

Step through a Cloud Bigtable codelab that teaches you how to avoid common schema design mistakes, import data, and then query and use it.

Google Cloud Basics
Creating a Cloud Bigtable instance

Create a Cloud Bigtable instance using command-line tools or the Cloud Console.

Quickstart using the cbt tool

Learn first-hand how to use the cbt command line to connect to a Cloud Bigtable instance, perform basic admin tasks, and read and write data in a table.

Google Cloud Basics
Migrating from HBase to Cloud Bigtable with minimal downtime

Use tooling designed to create Cloud Bigtable tables from HBase tables schemas, import snapshots of the HBase tables, and validate the integrity of migrated data.

Google Cloud Basics

Let Cloud Bigtable automatically add or remove nodes when usage changes, significantly lowering the risk of over-provisioning or under-provisioning your resources.

Google Cloud Basics
Customer-managed encryption keys (CMEK)

CMEK provides the ability to create and manage Bigtable instances using Google Cloud Key Management (KMS) encryption keys to protect your data at rest.

Google Cloud Basics
Cloud Bigtable for Cassandra users

Understand the similarities and differences between Cloud Bigtable and Apache Cassandra so you can migrate existing applications or build new ones using Bigtable.

APIs & Libraries
Cloud Bigtable client libraries

Work with Cloud Bigtable using a Google Cloud client library in your preferred programming language.

Google Cloud Basics
Optimize schema performance with Key Visualizer

Key Visualizer lets you see key access patterns in heatmap format to optimize your Cloud Bigtable schemas for improved performance.

Use cases

Use cases

Use case
Financial analysis

Build models based on historical behavior. Continually update fraud patterns and compare with real-time transactions. Store and consolidate market data, trade activity, and other data, such as social and transactional data.

Financial analysis use case diagram: Large grey rectangle labeled Google Cloud encompases, on the left, stacked boxes, top labeled Batch containing Time Series Files / Cloud Storage, bottom labeled Streaming containing Time Series Streaming / Pub/Sub. Arrows move right to Time Series Processing / Dataflow. Arrows right to 6 interconnected boxes: Storage / BigQuery, Storage/Cloud Bigtable, Storage/Cloud Storage, Machine Learning/AI Platform, Processing/ Dataproc, and Analysis/Datalab.
Use case

Ingest and analyze large volumes of time series data from sensors in real time, matching the high speeds of IoT data to track normal and abnormal behavior. Enable customers to build dashboards and drive analytics on their data in real time.

IoT use case diagram: From left to right, green rectangle labeled “Constrained Devices Non-TCP (e.g. BLE)” contains 3 device icons. Arrow flows right to pink rectangle labeled “Standard Devices HTTPs,” with 3 device icons. Arrow right to Google Cloud rectangle with Ingestion, Pipelines, Storage, Analytics, and Application & Presentation rectangles. Ingestion contains icons for Pub/Sub, Cloud Monitoring, Cloud Logging. Pipelines has Dataflow. Storage has Cloud Storage, Databases, Cloud Bigtable. Analytics has Dataflow, BigQuery, Dataproc, and Datalab. Application & Presentation has App Engine, Google Kubernetes, and Compute Engine. Arrows interconnect these 4 rectangles.
Use case

Integrate large volumes of unrefined data from many sources, typically to drive consistent customer activity across channels. Collect and compare large volumes of behavior data across customers to find common patterns that can drive recommendations and sales.

3 stacked boxes on left. 1 “Beacons proximity notifications.” 2 “Back Office Business Systems.” 3 “Mobile Devices Push Notifications.” 1 and 2 flow right to Google Cloud square containing boxes. First is labeled Messaging / Pub/Sub / Proximity Streams. Arrow right to box labeled Processing / Dataflow / Stream Processing. Arrow down to box labeled Messaging / Pub/Sub / Queued Notification. Arrow down to box labeled Notifications / App Engine / Push to Devices. Arrow moves left to 3rd box in the stack: Mobile Devices. From Processing box, arrows also point right to box labeled Events / Cloud Bigtable / Proximity Events and to box labeled Analytics / BigQuery / Data Warehouse



Cloud Bigtable is a fast, fully managed, massively scalable NoSQL database service. For detailed pricing information, please view the pricing guide.


Work with a partner with Bigtable expertise

Take advantage of our growing partner ecosystem to help you maximize value from Bigtable.