Databricks brings the data lake to google cloud platform

DataBricks brings the Data Lake to Google Cloud Platform

With its so-called lakehouse architecture, the benefits of Data Lakes and Data Warehouses should associate, DataBrick’s companies want to provide a central data and analysis platform. It should meet both the requirements of traditional business intelligence and SQL tools as well as more modern machine learning and data science applications. The lakehouse platform will also apply to users in the Google Cloud – and for the first time in a complete containerized cloud environment, as well as both providers announced now.

Flexible containerizing on the Google Kubernetes Engine

While two cloud implementations worldwide are already ready for use with Azure DataBricks and DataBricks on AWS, integration with the Google Cloud Platform (GCP) is to be completed and expected to be generally available from the second quarter. Thanks to the containerized deployment based on the Google Kubernetes Engine (GKE), DataBricks users are also available to the entire services of the full-length managed operating environment – for example, for the areas of security and compute as well as network guidelines.

In addition, a series of connectors relate users to rapid integration of other Google services such as BigQuery, Cloud Storage and Pub / Sub. For example, Databicks users under others have the possibility of expanding their lakehouse analysis functions to expand the platform widely available BigQuery options and to stop overall analyzes within the GCP. Data workflows created in Databicks can be used together with the data statements prepared in BigQuery and Cloud Storage also for the model training on Google’s AI Platform.

Further information on the narrower cooperation of DataBricks and Google Cloud has the joint acquire ready. Details on the integration of the lakehouse platform in GCP as well as to the available features can be found on the homepage of DataBricks.

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