Integrations with Cloud Bigtable

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

Google Cloud Platform services

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

BigQuery

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

To get started, see Querying Cloud Bigtable Data.

Cloud Dataflow

Google Cloud Dataflow is a cloud service and programming model for big data processing. Cloud Dataflow supports both batch and streaming processing using Java. Python is not yet supported. You can use Cloud Dataflow to process data that is stored in Cloud Bigtable or to store the output of your Cloud Dataflow pipeline.

To get started, see Dataflow Connector for Cloud Bigtable.

Cloud Dataproc

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

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

Big Data

This section describes Big Data products that Cloud Bigtable integrates with.

Apache Hadoop

Apache Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers. You can use Cloud Dataproc to create a Hadoop cluster, then run map/reduce jobs that read from and write to Cloud Bigtable.

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

Geospatial databases

This section describes geospatial databases that Cloud Bigtable integrates with.

GeoMesa

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

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

Graph databases

This section describes graph databases that Cloud Bigtable integrates with.

HGraphDB

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

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

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 Cloud Bigtable support, see the JanusGraph documentation.

Infrastructure management

This section describes infrastructure management tools that Cloud Bigtable integrates with.

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 Cloud Bigtable with Terraform, see Cloud Bigtable Instance and Cloud Bigtable Table in the Terraform documentation.

Time-series databases and monitoring

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

Heroic

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

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

OpenTSDB

OpenTSDB is a time-series database. With the AsyncBigtable library, OpenTSDB can use Cloud Bigtable to store its data.

For more information about running OpenTSDB with Cloud Bigtable support, see Pythian's blog post and the OpenTSDB documentation.

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Cloud Bigtable Documentation