How to load data from Exchange Rates Api to Databricks Lakehouse

Learn how to use Airbyte to synchronize your Exchange Rates Api data into Databricks Lakehouse within minutes.

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Set up a Exchange Rates Api connector in Airbyte

Connect to Exchange Rates Api or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Databricks Lakehouse for your extracted Exchange Rates Api data

Select Databricks Lakehouse where you want to import data from your Exchange Rates Api source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Exchange Rates Api to Databricks Lakehouse in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Exchange Rates Api as a source connector (using Auth, or usually an API key)
set up Databricks Lakehouse as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Exchange Rates Api

Used by tens of thousands of developers, Exchange Rates API provides accurate and reliable currency data instantly through its free, simple-to-use API interface. With more than 10 years of exceptional API uptime and support, developers trust Exchange Rates API to provide fast and accurate conversion rates for 160 different currencies as well as essential stock market data in JSON format. They have worked hard to achieve their mission of building a remarkably hardware efficient and reliable currency converter API.

What is Databricks Lakehouse

Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.

Integrate Exchange Rates Api with Databricks Lakehouse in minutes

Try for free now

Prerequisites

A Exchange Rates Api account to transfer your customer data automatically from.
A Databricks Lakehouse account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Exchange Rates Api and Databricks Lakehouse, for seamless data migration.

When using Airbyte to move data from Exchange Rates Api to Databricks Lakehouse, it extracts data from Exchange Rates Api using the source connector, converts it into a format Databricks Lakehouse can ingest using the provided schema, and then loads it into Databricks Lakehouse via the destination connector. This allows businesses to leverage their Exchange Rates Api data for advanced analytics and insights within Databricks Lakehouse, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Exchange Rates Api as a source connector

1. Go to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
2. Click on the "Create a new source" button and select "Exchange Rates API" from the list of available connectors.
3. Enter a name for your source and click on "Next".
4. Enter your Exchange Rates API access key in the "API Key" field.
5. Select the base currency you want to use for your exchange rates in the "Base Currency" field.
6. Choose the frequency at which you want to update your exchange rates in the "Sync Frequency" field.
7. Click on "Test" to ensure that your credentials are correct and that the connection is successful.
8. If the test is successful, click on "Create" to save your source and start syncing your exchange rates data.

Note: You can also customize your source settings by selecting the tables you want to sync, setting up incremental sync, and adding filters to your data.

Step 2: Set up Databricks Lakehouse as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the "Databricks Lakehouse" connector and click on it.
4. You will be prompted to enter your Databricks Lakehouse credentials, including your account name, personal access token, and workspace ID.
5. Once you have entered your credentials, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save" button to save your Databricks Lakehouse destination connector settings.
7. You can now use the Databricks Lakehouse connector to transfer data from your source connectors to your Databricks Lakehouse destination.
8. To set up a data transfer, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector credentials and configure your data transfer settings.
10. Once you have configured your source connector, select the Databricks Lakehouse connector as your destination and follow the prompts to configure your data transfer settings.
11. Click on the "Run" button to initiate the data transfer.

Step 3: Set up a connection to sync your Exchange Rates Api data to Databricks Lakehouse

Once you've successfully connected Exchange Rates Api as a data source and Databricks Lakehouse as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Exchange Rates Api from the dropdown list of your configured sources.
Select your destination: Choose Databricks Lakehouse from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Exchange Rates Api objects you want to import data from towards Databricks Lakehouse. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Exchange Rates Api to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your Exchange Rates Api data.

Use Cases to transfer your Exchange Rates Api data to Databricks Lakehouse

Integrating data from Exchange Rates Api to Databricks Lakehouse provides several benefits. Here are a few use cases:

Advanced Analytics: Databricks Lakehouse’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Exchange Rates Api data, extracting insights that wouldn't be possible within Exchange Rates Api alone.
Data Consolidation: If you're using multiple other sources along with Exchange Rates Api, syncing to Databricks Lakehouse allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Exchange Rates Api has limits on historical data. Syncing data to Databricks Lakehouse allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Databricks Lakehouse provides robust data security features. Syncing Exchange Rates Api data to Databricks Lakehouse ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Databricks Lakehouse can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Exchange Rates Api data.
Data Science and Machine Learning: By having Exchange Rates Api data in Databricks Lakehouse, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Exchange Rates Api provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Databricks Lakehouse, providing more advanced business intelligence options. If you have a Exchange Rates Api table that needs to be converted to a Databricks Lakehouse table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Exchange Rates Api account as an Airbyte data source connector.
Configure Databricks Lakehouse as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Exchange Rates Api to Databricks Lakehouse after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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Sync with Airbyte

Step 1: Set up Exchange Rates Api as a source connector

Note: You can also customize your source settings by selecting the tables you want to sync, setting up incremental sync, and adding filters to your data.

Step 2: Set up Databricks Lakehouse as a destination connector

Step 3: Set up a connection to sync your Exchange Rates Api data to Databricks Lakehouse

Once you've successfully connected Exchange Rates Api as a data source and Databricks Lakehouse as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Exchange Rates Api from the dropdown list of your configured sources.
Select your destination: Choose Databricks Lakehouse from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Exchange Rates Api objects you want to import data from towards Databricks Lakehouse. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Exchange Rates Api to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your Exchange Rates Api data.

How to Sync Exchange Rates Api to Databricks Lakehouse Manually

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Step 8:

FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Exchange Rates Api?

What data can you extract from Exchange Rates Api?

Exchange Rates API provides access to various types of data related to currency exchange rates. The API offers real-time and historical exchange rates for over 170 currencies, including cryptocurrencies. The following are the categories of data that the Exchange Rates API provides:

• Real-time exchange rates: The API provides real-time exchange rates for various currencies, which are updated every minute.
• Historical exchange rates: The API offers historical exchange rates for up to 10 years, allowing users to analyze trends and patterns in currency exchange rates.
• Currency conversion: The API allows users to convert one currency to another using the latest exchange rates.
• Time-series data: The API provides time-series data for exchange rates, allowing users to track changes in exchange rates over time.
• Currency metadata: The API provides metadata for various currencies, including their names, symbols, and ISO codes.
• Cryptocurrency data: The API provides real-time exchange rates for various cryptocurrencies, including Bitcoin, Ethereum, and Litecoin.

Overall, the Exchange Rates API provides a comprehensive set of data related to currency exchange rates, making it a valuable resource for businesses and individuals who need to track currency exchange rates.

How do I transfer data from Exchange Rates Api?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up Exchange Rates API to Databricks Lakehouse as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Exchange Rates API to Databricks Lakehouse and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Back to all tutorials

Warehouses and Lakes

Finance & Ops Analytics

How to load data from Exchange Rates Api to Databricks Lakehouse

Learn how to use Airbyte to synchronize your Exchange Rates Api data into Databricks Lakehouse within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

TL;DR

What is Exchange Rates Api

What is Databricks Lakehouse

Prerequisites

Step 1: Setup Exchange Rates Api

Step 2: Setup Databricks Lakehouse

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Exchange Rates Api and Databricks Lakehouse

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Exchange Rates Api as a source connector (using Auth, or usually an API key)
set up Databricks Lakehouse as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Exchange Rates Api

What is Databricks Lakehouse

Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.

Integrate Exchange Rates Api with Databricks Lakehouse in minutes

Try for free now

Prerequisites

A Exchange Rates Api account to transfer your customer data automatically from.
A Databricks Lakehouse account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Step 1: Set up Exchange Rates Api as a source connector

Note: You can also customize your source settings by selecting the tables you want to sync, setting up incremental sync, and adding filters to your data.

Step 2: Set up Databricks Lakehouse as a destination connector

Step 3: Set up a connection to sync your Exchange Rates Api data to Databricks Lakehouse

Once you've successfully connected Exchange Rates Api as a data source and Databricks Lakehouse as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Exchange Rates Api from the dropdown list of your configured sources.
Select your destination: Choose Databricks Lakehouse from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Exchange Rates Api objects you want to import data from towards Databricks Lakehouse. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Exchange Rates Api to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your Exchange Rates Api data.

Use Cases to transfer your Exchange Rates Api data to Databricks Lakehouse

Integrating data from Exchange Rates Api to Databricks Lakehouse provides several benefits. Here are a few use cases:

Advanced Analytics: Databricks Lakehouse’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Exchange Rates Api data, extracting insights that wouldn't be possible within Exchange Rates Api alone.
Data Consolidation: If you're using multiple other sources along with Exchange Rates Api, syncing to Databricks Lakehouse allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Exchange Rates Api has limits on historical data. Syncing data to Databricks Lakehouse allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Databricks Lakehouse provides robust data security features. Syncing Exchange Rates Api data to Databricks Lakehouse ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Databricks Lakehouse can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Exchange Rates Api data.
Data Science and Machine Learning: By having Exchange Rates Api data in Databricks Lakehouse, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Exchange Rates Api provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Databricks Lakehouse, providing more advanced business intelligence options. If you have a Exchange Rates Api table that needs to be converted to a Databricks Lakehouse table, Airbyte can do that automatically.