Integrations with Bigtable

This page describes integrations between Cloud Bigtable and other products and services.

Google Cloud services

This section describes the Google Cloud services that Bigtable integrates with.

BigQuery

BigQuery is Google's fully managed, petabyte-scale, low-cost analytics data warehouse. You can use BigQuery to query data stored in Bigtable.

To get started, see Querying Bigtable Data.

Cloud Asset Inventory

Cloud Asset Inventory, which provides inventory services based on a time series database, supports and returns Bigtable resources types. For a complete list, see Supported resource types.

Cloud Functions

Cloud Functions is an event-driven serverless compute platform that integrates with Bigtable.

The tutorial Using Bigtable with Cloud Functions demonstrates how to write, deploy, and trigger an HTTP Bigtable in Node.js, Python, and Go.

Dataflow

Dataflow is a cloud service and programming model for big data processing. Dataflow supports both batch and streaming processing. You can use Dataflow to process data that is stored in Bigtable or to store the output of your Dataflow pipeline. You can also use Dataflow templates to export and import your data as Avro, Parquet, or SequenceFiles.

Note: The Python client library for Bigtable supports Dataflow writes but not reads.

To get started, see Bigtable Beam connector .

Dataproc

Dataproc provides Apache Hadoop and related products as a managed service in the cloud. With Dataproc, you can run Hadoop jobs that read from and write to Bigtable.

For an example of a Hadoop MapReduce job that uses Bigtable, see the /java/dataproc-wordcount directory in the GitHub repository GoogleCloudPlatform/cloud-bigtable-examples.

Big Data

This section describes Big Data products that Bigtable integrates with.

Apache Hadoop

Apache Hadoop is a framework that enables distributed processing of large data sets across clusters of computers. You can use Dataproc to create a Hadoop cluster, then run MapReduce jobs that read from and write to Bigtable.

For an example of a Hadoop MapReduce job that uses Bigtable, see the /java/dataproc-wordcount directory in the GitHub repository GoogleCloudPlatform/cloud-bigtable-examples.

StreamSets Data Collector

StreamSets Data Collector is a data-streaming application that you can configure to write data to Bigtable. StreamSets provides a Bigtable library in its GitHub repository at streamsets/datacollector.

Geospatial databases

This section describes geospatial databases that Bigtable integrates with.

GeoMesa

GeoMesa is a distributed spatio-temporal database that supports spatial querying and data manipulation. GeoMesa can use Bigtable to store its data.

For more information about running GeoMesa with Bigtable support, see the GeoMesa documentation.

Note: This integration was developed independently by a third party. Google is not affiliated with, and does not endorse, this integration.

Graph databases

This section describes graph databases that Bigtable integrates with.

HGraphDB

HGraphDB is a client layer for using Apache HBase or Bigtable as a graph database. It implements the Apache TinkerPop 3 interfaces.

For more information about running HGraphDB with Bigtable support, see the HGraphDB documentation.

Note: This integration was developed independently by a third party. Google is not affiliated with, and does not endorse, this integration.

JanusGraph

JanusGraph is a scalable graph database. It is optimized for storing and querying graphs containing hundreds of billions of vertices and edges.

For more information about running JanusGraph with Bigtable support, see Running JanusGraph with Bigtable or the JanusGraph documentation.

Infrastructure management

This section describes infrastructure management tools that Bigtable integrates with.

Pivotal Cloud Foundry

Pivotal Cloud Foundry is an application development and deployment platform that offers the ability to bind an application to Bigtable.

Terraform

Terraform is an open source tool that codifies APIs into declarative configuration files. These files can be shared among team members, treated as code, edited, reviewed, and versioned.

For more information about using Bigtable with Terraform, see Bigtable Instance and Bigtable Table in the Terraform documentation.

Time-series databases and monitoring

This section describes time-series databases and monitoring tools that Bigtable integrates with.

Heroic

Heroic is a monitoring system and time-series database. Heroic can use Bigtable to store its data.

For more information about Heroic, see the GitHub repository spotify/heroic, as well as the documentation for configuring Bigtable and configuring metrics.

Note: This integration was developed independently by a third party. Google is not affiliated with, and does not endorse, this integration.

OpenTSDB

OpenTSDB is a time-series database that can use Bigtable for storage. Monitoring time-series data with OpenTSDB on Bigtable and GKE shows how to use OpenTSDB to collect, record, and monitor time-series data on Google Cloud. The OpenTSDB documentation provides additional information to help you get started.