As a data engineer, you hold all the cards to make data easily accessible to your business teams. Your team just requested a MariaDB to Databricks connection on priority. We know you don’t wanna keep your data scientists and business analysts waiting to get critical business insights. As the most direct approach, you can go straight for the CSV files exporting if this is a one-time thing. Or, hunt for a no-code tool that fully automates & manages data integration for you while you focus on your core objectives.

Well, look no further. With this article, get a step-by-step guide to connecting MariaDB to Databricks effectively and quickly delivering data to your marketing team. 

Replicate Data from MariaDB to Databricks Using CSV

To start replicating data from MariaDB to Databricks, firstly, you need to export data as CSV files from MariaDB, then import the CSV files into Databricks and modify your data according to the needs.

  • Step 1: Using a general format, you can export the database as CSV. Below is the command in general format to export your data: 
Select field from table_name
INTO OUTFILE '/path/to/save/filename.csv'
FIELDS ENCLOSED BY ''
TERMINATED BY ','
ESCAPED BY '"'
LINES TERMINATED BY '\n';
  • Step 2:  In the Databricks UI, you can find and work with data by navigating the sidebar menu. To create a table, you can either browse your files from the local computer or drag your CSV files into the drop zone. Your path will look something like this: /FileStore/tables/<fileName>-<integer>.<fileType>. Once uploaded, you can simply view your data by clicking the Create Table with UI button.
MariaDB to Databricks: Import as CSV
Image Source
  • Step 3: After you upload the CSV data to Databricks, you can read and modify the data.
    • To preview a cluster, click on the Preview Table after selecting it. Databricks now lets you read your CSV data. 
    • In Databricks, data types are string by default. You can choose the data type from a list of options. 
    • The left navigation bar can help you modify the data easily. To create a table, click the “Create Table” button on the left navigation bar. 
    • Once all the table settings have been configured, click the “Create Table” button to finish.
    • The CSV files can be accessed from the cluster where you have stored that file.

This 3-step process using CSV files is a great way to effectively replicate data from MariaDB to Databricks. It is optimal for the following scenarios:

  • One-Time Data Replication: When your marketing team needs the MariaDB data only once in a long period of time. 
  • No Data Transformation Required: If there is a negligible need for data transformation and your data is standardized, then this method is ideal. 

In the following scenarios, using CSV files might be cumbersome and not a wise choice:

  • Data Mapping: Only basic data can be moved. Complex configurations cannot take place. There is no distinction between text and numeric values and null and quoted values.
  • Frequent changes in Source Data: To achieve two-way synchronization, the entire process must be run frequently to access updated data on the destination. 
  • Time Consuming:  If you plan to export your data frequently, the CSV method might not be the best choice since it takes time to recreate the data using CSV files. 

Automate the Data Replication process using a No-Code Tool

You can use automated pipelines to avoid such challenges. Here, are the following benefits:

  • Automated pipelines allow you to focus on core engineering objectives while your business teams can directly work on reporting without any delays or data dependency on you.
  • Automated pipelines provide a beginner-friendly UI that saves the engineering teams’ bandwidth from tedious data preparation tasks.

For instance, here’s how Hevo, a cloud-based ETL tool, makes MariaDB to Databricks data replication ridiculously easy:

Step 1: Configure MariaDB as a Source

Authenticate and Configure your MariaDB Source.

Image Source

Step 2: Configure Databricks as a Destination

In the next step, we will configure Databricks as the destination.

Step 3: All Done to Setup Your ETL Pipeline

Once your MariaDB to Databricks ETL Pipeline is configured, Hevo will collect new and updated data from MariaDB every five minutes (the default pipeline frequency) and duplicate it into Databricks. Depending on your needs, you can adjust the pipeline frequency from 5 minutes to an hour.

Data Replication Frequency

Default Pipeline FrequencyMinimum Pipeline FrequencyMaximum Pipeline FrequencyCustom Frequency Range (Hrs)
1 Hr15 Mins24 Hrs1-24

In a matter of minutes, you can complete this No-Code & automated approach of connecting MariaDB to Databricks using Hevo and start analyzing your data.

Hevo offers 150+ plug-and-play connectors(Including 40+ free sources). It efficiently replicates your data from MariaDB to Databricks, databases, data warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo’s fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss. It also enriches the data and transforms it into an analysis-ready form without having to write a single line of code.

Hevo’s reliable data pipeline platform enables you to set up zero-code and zero-maintenance data pipelines that just work. By employing Hevo to simplify your data integration needs, you get to leverage its salient features:

  • Fully Managed: You don’t need to dedicate time to building your pipelines. With Hevo’s dashboard, you can monitor all the processes in your pipeline, thus giving you complete control over it.
  • Data Transformation: Hevo provides a simple interface to cleanse, modify, and transform your data through drag-and-drop features and Python scripts. It can accommodate multiple use cases with its pre-load and post-load transformation capabilities.
  • Faster Insight Generation: Hevo offers near real-time data replication, so you have access to real-time insight generation and faster decision-making. 
  • Schema Management: With Hevo’s auto schema mapping feature, all your mappings will be automatically detected and managed to the destination schema.
  • Scalable Infrastructure: With the increase in the number of sources and volume of data, Hevo can automatically scale horizontally, handling millions of records per minute with minimal latency.
  • Transparent pricing: You can select your pricing plan based on your requirements. Different plans are clearly put together on its website, along with all the features it supports. You can adjust your credit limits and spend notifications for any increased data flow.
  • Live Support: The support team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

Take our 14-day free trial to experience a better way to manage data pipelines.

Get started for Free with Hevo!

What Can You Achieve by Migrating Your Data from MariaDB to Databricks?

Here’s a little something for the data analyst on your team. We’ve mentioned a few core insights you could get by replicating data from MariaDB to Databricks. Does your use case make the list?

  • Aggregate the data of individual interactions of the product for any event. 
  • Finding the customer journey within the product.
  • Integrating transactional data from different functional groups (Sales, marketing, product, Human Resources) and finding answers. For example:
    • Which Development features were responsible for an App Outage in a given duration?
    • Which product categories on your website were most profitable?
    • How does Failure Rate in individual assembly units affect Inventory Turnover?

Summing It Up

Exporting and importing CSV files is the right path for you when your team needs data from MariaDB once in a while. However, a custom ETL solution becomes necessary for the increasing data demands of your product or marketing channel. You can free your engineering bandwidth from these repetitive & resource-intensive tasks by selecting Hevo’s 150+ plug-and-play integrations.

Visit our Website to Explore Hevo

Saving countless hours of manual data cleaning & standardizing, Hevo’s pre-load data transformations get it done in minutes via a simple drag n drop interface or your custom python scripts. No need to go to your data warehouse for post-load transformations. You can simply run complex SQL transformations from the comfort of Hevo’s interface and get your data in the final analysis-ready form. 

Want to take Hevo for a ride? Sign Up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Share your experience of replicating data from MariaDB to Databricks! Let us know in the comments section below!

Harsh Varshney
Research Analyst, Hevo Data

Harsh comes with experience in performing research analysis who has a passion for data, software architecture, and writing technical content. He has written more than 100 articles on data integration and infrastructure.

No-code Data Pipeline for Databricks