Google Drive to Databricks Integration: 3 Easy Steps

This article will unveil a 3-step process to set up Google Drive to Databricks Integration. We will build an ETL pipeline to replicate Google Drive data on Databricks.

By employing Hevo ETL pipelines, you will save hours. The need for an extensive data preparation process will not exist, allowing you to concentrate on core business activities to reach new heights of profitability.

Read along to learn more exciting aspects of Google Drive to Databricks Integration. 

What is Google Drive?

Google Drive is a cloud-based storage service that enables users to store and access files online. The service syncs stored documents, photos and more across all the user’s devices, including mobile devices, tablets and PCs.

What is Databricks?

Databricks is a unified, open analytics platform for building, deploying, sharing, and maintaining enterprise-grade data, analytics, and AI solutions at scale. The Databricks Data Intelligence Platform integrates with cloud storage and security in your cloud account and manages and deploys cloud infrastructure on your behalf.

Why Connect Google Drive to Databricks?

As organizations expand, it is challenging to consolidate data into a single source of truth for better reporting and analysis.

By replicating your Google Drive data to Databricks, you can take advantage of customized dashboards which provide you and your team with actionable insights in a visualized format.

Google Drive to Databricks Integration enables an organization-wide data unification with a consistent format. You can leverage Hevo, a No-Code Data Pipeline, to make the data replication process a cakewalk.

Let’s take a quick look at what Google Drive to Databricks Integration has to offer:

• Complete Analysis With a 360-degree View: It allows you to access advanced reports for additional insights from your Google Drive data.
• Combine & Assemble to Get Customized Information: Keep track of your organization-wide data by extracting relevant data from Google Drive and combining it with data from other sources.
• Separate Computing and Storage: Using Google Drive enables storage scalability for unprocessed and processed data that flows from disparate sources.
• Support for Transactions: Data lakes frequently struggle to handle several users and groups reading and publishing data simultaneously. When reading and writing this data concurrently, support for Atomicity, Consistency, Isolation, and Durability (ACID) transactions is necessary to ensure that there are no conflicts among various participants. This ACID support is natively provided by Databricks when using the open-source format Delta Lake.
• Say No to CSV Files and Python Scripts: Focus on creating a data stack and improving data quality rather than writing custom code to integrate Sales and Marketing technology. T

How to connect Google Drive to Databricks Using Hevo?

Step 1: Configure Google Drive as a Source

Note: You can also perform data transformations using either Python-based or drag-and-drop transformations, which does not require you to be a tech freak.

Step 2: Configure Databricks as a Destination

Step 3: Finish setting up your ETL pipeline.

Data Replication Frequency

Default Pipeline Frequency	Minimum Pipeline Frequency	Maximum Pipeline Frequency	Custom Frequency Range (Hrs)
5 Mins	5 Mins	24 Hrs	1-24

Now that you’ve configured your Google Drive as your data source & Databricks as your data destination, you have successfully created your data pipeline, which is ready to rock. You can also schedule your pipeline to run at different frequencies; click here to learn more.

Conclusion

This post has touched the surface of the many critical aspects of setting up Google Drive to Databricks Integration.

There is rapid growth and prominence of Databricks as a significant player when it comes to managing massive datasets. By removing the silos that might complicate the data, Databrick’s solution enables organizations to utilize their data fully. 

Many organizations are still debating whether to Build vs. Buy ETL pipelines. Numerous factors such as team size, clientele served, and company size influences an organization’s decision.

Quick Tip: Focus on performance improvement, self-service search, and discovery as you move away from traditional Data federation technologies to Data warehouses. Invest more to analyze data thoroughly than spending time searching for it.

Experience fully automated, hassle-free data replication for Google Drive by immediately starting your journey with Hevo and Databricks.

Share your experience understanding the Google Drive to Databricks Integration in the comments below! We would love to hear your thoughts.

Try Hevo today for free and save your engineering resources.

Sign Up For a 14-day Free Trial Today

Frequently Asked Questions