Moving data from MySQL to Elasticsearch 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 MySQL as a source connector (using Auth, or usually an API key)
2. set up Elasticsearch as a destination connector
3. 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 MySQL

MySQL is an SQL (Structured Query Language)-based open-source database management system. An application with many uses, it offers a variety of products, from free MySQL downloads of the most recent iteration to support packages with full service support at the enterprise level. The MySQL server, while most often used as a web database, also supports e-commerce and data warehousing applications and more.

What is Elasticsearch

Elasticsearch is a powerful search and analytics engine that is designed to handle large amounts of data in real-time. It is an open-source, distributed, and scalable search engine that is built on top of the Apache Lucene search library. Elasticsearch is used to search, analyze, and visualize data in real-time, making it an ideal tool for businesses and organizations that need to process large amounts of data quickly. Elasticsearch is designed to be highly scalable and can be used to index and search data across multiple servers. It is also highly customizable, allowing users to configure it to meet their specific needs. Elasticsearch is commonly used for log analysis, full-text search, and business analytics. One of the key features of Elasticsearch is its ability to handle unstructured data, such as text, images, and videos. It uses a powerful search algorithm to analyze and index this data, making it easy to search and retrieve information quickly. Elasticsearch also supports a wide range of data formats, including JSON, CSV, and XML, making it easy to integrate with other data sources. Overall, Elasticsearch is a powerful tool that can help businesses and organizations to process and analyze large amounts of data quickly and efficiently.

Prerequisites

1. A MySQL account to transfer your customer data automatically from.
2. A Elasticsearch account.
3. 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 MySQL and Elasticsearch , for seamless data migration.

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

Step 1: Set up MySQL as a source connector

1. Open the Airbyte UI and navigate to the "Sources" tab.

2. Click on the "Add Source" button and select "MySQL" from the list of available sources.

3. Enter a name for your MySQL source and click on the "Next" button.

4. Enter the necessary credentials for your MySQL database, including the host, port, username, and password.

5. Select the database you want to connect to from the drop-down menu.

6. Choose the tables you want to replicate data from by selecting them from the list.

7. Click on the "Test" button to ensure that the connection is successful.

8. If the test is successful, click on the "Create" button to save your MySQL source configuration.

9. You can now use your MySQL connector to replicate data from your MySQL database to your destination of choice.

Step 2: Set up Elasticsearch 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 Elasticsearch connector and click on it.
4. You will be prompted to enter your Elasticsearch connection details, including the host URL, port number, and any authentication credentials.
5. Once you have entered your connection details, click on the "Test" button to ensure that your connection is working properly.
6. If the test is successful, click on the "Save" button to save your Elasticsearch connector settings.
7. You can now use this connector to send data from your Airbyte sources to your Elasticsearch database.
8. To set up a pipeline, navigate to the "Sources" tab and select the source you want to use.
9. Click on the "Create New Connection" button and select your Elasticsearch connector from the list.
10. Follow the prompts to map your source data to your Elasticsearch database fields and save your pipeline.

‘Step 3: Set up a connection to sync your data from MySQL to Elasticsearch

Once you've successfully connected MySQL as a data source and Elasticsearch as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
2. Choose your source: Select MySQL from the dropdown list of your configured sources.
3. Select your destination: Choose Elasticsearch from the dropdown list of your configured destinations.
4. 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.
5. Select the data to sync: Choose the specific MySQL objects you want to import data from towards Elasticsearch . You can sync all data or select specific tables and fields.
6. 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.
7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from MySQL to Elasticsearch according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Elasticsearch data warehouse is always up-to-date with your MySQL data.

Use Cases to transfer your MySQL data to Elasticsearch

Integrating data from MySQL to Elasticsearch provides several benefits. Here are a few use cases:

1. Advanced Analytics: Elasticsearch's powerful data processing capabilities enable you to perform complex queries and data analysis on your MySQL data, extracting insights that wouldn't be possible within MySQL alone.
2. Data Consolidation: If you're using multiple other sources along with MySQL, syncing to Elasticsearch 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.
3. Historical Data Analysis: MySQL has limits on historical data. Syncing data to Elasticsearch allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: Elasticsearch provides robust data security features. Syncing MySQL data to Elasticsearch ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: Elasticsearch can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding MySQL data.
6. Data Science and Machine Learning: By having MySQL data in Elasticsearch , you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While MySQL provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Elasticsearch, providing more advanced business intelligence options. If you have a MySQL table that needs to be converted to a Elasticsearch table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a MySQL account as an Airbyte data source connector.
2. Configure Elasticsearch as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from MySQL to Elasticsearch 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!