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Send Data from Databricks to Databases
Databricks is a cloud data platform built to store, process, and analyze big data for analytics, AI, and any use case. With over 8850 companies using Databricks in 2023, it has become one of the most popular tools for collecting and manipulating data.
Databricks works on distributed systems, meaning the workload is automatically dispersed across multiple processors and can scale to any requirement, increasing efficiency and data processing power. This increased efficiency reduces resource load and accelerates data speed and value across the business. Databricks’ ability to process huge datasets enables workloads that were previously difficult to work with.
However, collecting data in warehouses, databases, and data lakes does not automatically make the data useful. Seamless integration to a tool like Databricks in order to derive value from the data is an essential part of a unified data solution, and sending data to and from Databricks can be done simply and easily with Nexla.
Follow along with this guide as we show you how to send data automatically from Databricks to any database. In this example, we’ve picked MongoDB, but the steps will be similar for any database.
Connecting to Databricks
- Select the source and authenticate your Databricks credential. Begin by going to “Flows” and clicking “Create New Source.”
- Search for Databricks and add it as your data source.
- You’ll need to enter credentials, or accept credentials that have been shared with you, then click Next.
- Select your dataset. In this example, we will use the Table Mode tab to select the “customers” table listed under “samples”. You can alternatively select Nexla’s Query Mode tab to write custom SQL queries to specify your data source. In Query Mode, you can use SQL queries of any level of complexity to specify your exact dataset instead of selecting an entire Databricks table. The SQL queries are pushed down to leverage the high-performance Databricks SQL engine, and Nexla will process the result of an SQL query as the data source. Once you’ve selected your dataset, you’ll be able to configure the source to customize your data flow and fetching schedule; then, simply click “Create.”
- The resulting data from the selection in the previous step will automatically be scanned to generate a Nexset. Click “Done”.
Send to a Database
Now we’ll set the data to be automatically sent to a database, API, or delivered in any format. In this example, we’ll send the data to MongoDB, a scalable, document-oriented NoSQL database
- Go to Flows, select the new Databricks flow, and select the send to destination button.
- Select your destination. In this case, we’re using MongoDB.
- Authenticate your credentials, as we did with the source, then click “Next”.
- Select the location to send the data to, then click “Next”.
- Now you’ll be able to choose which data to send. Once you’ve selected the data, click “Save”.
- Choose to Activate This Flow, then click “Done”.
Databricks is one of the most popular cloud-based data engineering platforms currently on the market. This easy-to-use cloud data platform provides robust data storage and manipulation capabilities. Being able to easily send data to and from it is an essential skill for any enterprise currently using Databricks.
With a tool like Nexla, flows can be done in minutes with a few clicks, meaning that little to no technical knowledge or engineering background is required to move data. This enables anyone in your organization to get the data they need or send that data to where they need it.
If you’re ready to integrate your data and put it in the hands of the people who use it, get a demo or book your free data strategy consultation today and learn how much more your data can do when everyone has access. For more on data, check out the other articles on Nexla’s blog.
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