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Google BigQuery is a cloud database like system that is used mostly for querying data powered by Google Cloud Platform (GCP).

Stambia Data Integration allows to work with Google BigQuery databases to produce fully customized Integration Processes.

The database structure can be entirely reversed in Metadata and then used in Mappings and Processes to design and adapt the business rules to meet the user's requirements.

Prerequisites:
  • Stambia DI Designer S18.3.8 or higher
  • Stambia DI Runtime S17.4.7 or higher
  • Java 1.8

Note:

Stambia DI is a flexible and agile solution. It can be quickly adapted to your needs.

If you have any question, any feature request or any issue, do not hesitate to contact us.

This component may require a dedicated license.

Please contact the Stambia support team if you have any doubt and if you need to use it in a production environment.

 

Download

You can find below the necessary material to work with Google BigQuery in Stambia DI

Name Description More Information Download
Google BigQuery Connector

Stambia DI Google BigQuery connector.

Installation procedure

Release notes

download

previous releases

Generic Templates Package containing the generic Templates Upgrade procedure download

previous releases

Google BigQuery Templates Package containing the Google BigQuery Templates

Upgrade procedure

Release notes

download

previous releases

Demonstration Project A project that demonstrates most of the features through examples of Mappings and Processes   download

 

To learn how to install and use Google BigQuery in Stambia DI, have a look at the following getting started article.

 

Supported features

You can find below an overview of what Stambia DI can do with Google BigQuery databases

Name Description
Reverse

The database structure can be reversed in a dedicated Metadata

Integration methods

Data can be sent to Google BigQuery with the following methods:

  • direct: data is directly sent to Google BigQuery
  • storage: data is extracted to a file which is sent to Google Storage and then loaded into Google BigQuery through Google's loader. This offers better performances on large set of data.
Storage methods

When integrating data into Google BigQuery using the storage method, you have the choice of how it should be done:

  • stream: Data is streamed directly in the Google Storage Bucket.
  • localfile: Data is first exported to a local temporary file, which is then sent to the defined Google Storage Bucket.

Depending on the amount of data sent and network quality, for instance, one method or the other can have better performances

Reading data from Google BigQuery The connector supports reading data from Google BigQuery to load it into another database, file, ...
Query Language

Stambia's Google BigQuery connector is using Standard SQL as default query mode.

All statements supported by Google BigQuery's Standard SQL can therefore be used seamlessly without any particular configuration.

Data consultation The connector supports consulting Google BigQuery data directly from the Designer.

 

 

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