TL;DR
The most prominent ETL and ELT tools to transfer data from MySQL include:
These ETL and ELT tools help in extracting data from MySQL and other sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities. Airbyte distinguishes itself by offering both a self-hosted open-source platform and a Cloud one..
What is MySQL ETL?
MySQL ETL is a process where data is extracted from MySQL databases, transformed into a suitable format, and loaded into a target system. It could be like extracting customer data from MySQL, converting currencies and dates to standardized formats, and loading it into a data warehouse.
How data integration from MySQL to a data warehouse can help
Companies might do MySQL ETL for several reasons:
- Business intelligence: MySQL data may need to be loaded into a data warehouse for analysis, reporting, and business intelligence purposes.
- Data Consolidation: Companies may need to consolidate data with other systems or applications to gain a more comprehensive view of their business operations
- Compliance: Certain industries may have specific data retention or compliance requirements, which may necessitate extracting data for archiving purposes.
Overall, ETL from MySQL allows companies to leverage the data for a wide range of business purposes, from integration and analytics to compliance and performance optimization.
Criterias to select the right MySQL ETL solution for you
As a company, you don't want to use one separate data integration tool for every data source you want to pull data from. So you need to have a clear integration strategy and some well-defined evaluation criteria to choose your MySQL ETL solution.
Here is our recommendation for the criteria to consider:
- Connector need coverage: does the ETL tool extract data from all the multiple systems you need, should it be any cloud app or Rest API, relational databases or noSQL databases, csv files, etc.? Does it support the destinations you need to export data to - data warehouses, databases, or data lakes?
- Connector extensibility: for all those connectors, are you able to edit them easily in order to add a potentially missing endpoint, or to fix an issue on it if needed?
- Ability to build new connectors: all data integration solutions support a limited number of data sources.
- Support of change data capture: this is especially important for your databases.
- Data integration features and automations: including schema change migration, re-syncing of historical data when needed, scheduling feature
- Efficiency: how easy is the user interface (including graphical interface, API, and CLI if you need them)?
- Integration with the stack: do they integrate well with the other tools you might need - dbt, Airflow, Dagster, Prefect, etc. - ?
- Data transformation: Do they enable to easily transform data, and even support complex data transformations? Possibly through an square integration with dbt
- Level of support and high availability: how responsive and helpful the support is, what are the average % successful syncs for the connectors you need. The whole point of using ETL solutions is to give back time to your data team.
- Data reliability and scalability: do they have recognizable brands using them? It also shows how scalable and reliable they might be for high-volume data replication.
- Security and trust: there is nothing worse than a data leak for your company, the fine can be astronomical, but the trust broken with your customers can even have more impact. So checking the level of certification (SOC2, ISO) of the tools is paramount. You might want to expand to Europe, so you would need them to be GDPR-compliant too.
Are Native MySQL ETL Tools Useful?
Native MySQL ETL tools like mysqldump and mysqlimport are useful for basic data movement tasks and small-to-medium scale operations. mysqldump works well for database backups and simple data migrations, while mysqlimport handles basic data loading. However, they lack advanced transformation capabilities, have limited scheduling options, and don't scale well for complex ETL pipelines or real-time data processing needs. So, third-party tools are recommended for a good MySQL ETL workflow.
Top 10 MySQL ETL tools
Here are the top MySQL ETL tools based on their popularity and the criteria listed above:
1. Airbyte
Airbyte is an open-source platform that supports MySQL ETL data pipelines through pre-built connectors. It handles both batch and incremental syncs, making it suitable for real-time data replication and historical data loads from MySQL databases.
Deployment options:
- Airbyte Cloud (managed service)
- Self-hosted
Key features:
- CDC support for MySQL
- Custom transformation using dbt
- 300+ pre-built source and destination connectors
- Point-and-click pipeline configuration
- Incremental sync modes
- Schema change detection and handling
- Custom connector development
- 99% SLA
2. Fivetran
Fivetran is a cloud-native ELT service that offers automated MySQL data syncs. It focuses on zero-maintenance pipelines with automatic schema migration handling and built-in error recovery. However, it doesn't offer as much flexibility as an open-source MySQL ETL tool would.
Deployment options: Cloud-hosted
Key features
- Built-in data normalization
- Enterprise-grade security
- Historical data syncs
- Log-based CDC replication
- Automatic failover handling
Fivetran charges for monthly active rows (in other words, the number of rows that have been edited or added in a given month) and are often considered very expensive. Here are more critical insights on the key differentiations between Airbyte and Fivetran.
3. Stitch Data
Stitch Data is another cloud-first MySQL ETL tool. It focuses on developer-centric features with extensive API support and integrates easily with modern data stack components.
Deployment: Cloud
Key features:
- Scheduling options
- Monitoring and alerting
- REST API access
- Modern security features
Given the lack of quality and reliability in their connectors and subpar support, Stitch has adopted a low-cost approach. Here are more insights on the differentiations between Airbyte and Stitch and between Fivetran and Stitch.
Other potential services
4. Matillion
Matillion is a self-hosted ELT solution, created in 2011. It supports about 100 connectors and provides all extract, load and transform features. Matillion is used by 500+ companies across 40 countries.
What's unique about Matillion?
Being self-hosted means that Matillion ensures your data doesn’t leave your infrastructure and stays on premise. However, you might have to pay for several Matillion instances if you’re multi-cloud. Also, Matillion has verticalized its offer from offering all ELT and more. So Matillion doesn't integrate with other tools such as dbt, Airflow, and more.
Here are more insights on the differentiations between Airbyte and Matillion.
5. Airflow
Apache Airflow is an open-source workflow management tool. Airflow is not an ETL solution but you can use Airflow operators for data integration jobs. Airflow started in 2014 at Airbnb as a solution to manage the company's workflows. Airflow allows you to author, schedule and monitor workflows as DAG (directed acyclic graphs) written in Python.
What's unique about Airflow?
Airflow requires you to build data pipelines on top of its orchestration tool. You can leverage Airbyte for the data pipelines and orchestrate them with Airflow, significantly lowering the burden on your data engineering team.
Here are more insights on the differentiations between Airbyte and Airflow.
6. Talend
Talend is a data integration platform that offers a comprehensive solution for data integration, data management, data quality, and data governance.
What’s unique with Talend?
What sets Talend apart is its open-source architecture with Talend Open Studio, which allows for easy customization and integration with other systems and platforms. However, Talend is not an easy solution to implement and requires a lot of hand-holding, as it is an Enterprise product. Talend doesn't offer any self-serve option.
7. Pentaho
Pentaho is an ETL and business analytics software that offers a comprehensive platform for data integration, data mining, and business intelligence. It offers ETL, and not ELT and its benefits.
What is unique about Pentaho?
What sets Pentaho data integration apart is its original open-source architecture, which allows for easy customization and integration with other systems and platforms. Additionally, Pentaho provides advanced data analytics and reporting tools, including machine learning and predictive analytics capabilities, to help businesses gain insights and make data-driven decisions.
However, Pentaho is also an Enterprise product, so hard to implement without any self-serve option.
8. Informatica PowerCenter
Informatica PowerCenter is an ETL tool that supported data profiling, in addition to data cleansing and data transformation processes. It was also implemented in their customers' infrastructure, and is also an Enterprise product, so hard to implement without any self-serve option.
9. Microsoft SQL Server Integration Services (SSIS)
MS SQL Server Integration Services is the Microsoft alternative from within their Microsoft infrastructure. It offers ETL, and not ELT and its benefits.
10. Singer
Singer is also worth mentioning as the first open-source JSON-based ETL framework. It was introduced in 2017 by Stitch (which was acquired by Talend in 2018) as a way to offer extendibility to the connectors they had pre-built. Talend has unfortunately stopped investing in Singer’s community and providing maintenance for the Singer’s taps and targets, which are increasingly outdated, as mentioned above.
All those ETL tools are not specific to MySQL, you might also find some other specific data loader for MySQL data. But you will most likely not want to be loading data from only MySQL in your data stores.
Which data can you extract from MySQL?
MySQL provides access to a wide range of data types, including:
1. Numeric data types: These include integers, decimals, and floating-point numbers.
2. String data types: These include character strings, binary strings, and text strings.
3. Date and time data types: These include date, time, datetime, and timestamp.
4. Boolean data types: These include true/false or yes/no values.
5. Spatial data types: These include points, lines, polygons, and other geometric shapes.
6. Large object data types: These include binary large objects (BLOBs) and character large objects (CLOBs).
7. Collection data types: These include arrays, sets, and maps.
8. User-defined data types: These are custom data types created by the user.
Overall, MySQL's API provides access to a wide range of data types, making it a versatile tool for managing and manipulating data in a variety of applications.
How to start pulling data in minutes from MySQL
If you decide to test Airbyte, you can start analyzing your MySQL data within minutes in three easy steps:
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 a destination for your extracted MySQL data
Choose from one of 50+ destinations where you want to import data from your MySQL source. This can be a cloud data warehouse, data lake, database, cloud storage, or any other supported Airbyte destination.
Step 3: Configure the MySQL data pipeline in Airbyte
Once you've set up both the source and destination, you need to configure the connection. This includes selecting the data you want to extract - streams and columns, all are selected by default -, the sync frequency, where in the destination you want that data to be loaded, among other options.
And that's it! It is the same process between Airbyte Open Source that you can deploy within 5 minutes, or Airbyte Cloud which you can try here, free for 14-days.
Conclusion
This article outlined the criteria that you should consider when choosing a data integration solution for MySQL ETL/ELT. Based on your requirements, you can select from any of the top 10 ETL/ELT tools listed above. We hope this article helped you understand why you should consider doing MySQL ETL and how to best do it.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Frequently Asked Questions
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.
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.
MySQL provides access to a wide range of data types, including:
1. Numeric data types: These include integers, decimals, and floating-point numbers.
2. String data types: These include character strings, binary strings, and text strings.
3. Date and time data types: These include date, time, datetime, and timestamp.
4. Boolean data types: These include true/false or yes/no values.
5. Spatial data types: These include points, lines, polygons, and other geometric shapes.
6. Large object data types: These include binary large objects (BLOBs) and character large objects (CLOBs).
7. Collection data types: These include arrays, sets, and maps.
8. User-defined data types: These are custom data types created by the user.
Overall, MySQL's API provides access to a wide range of data types, making it a versatile tool for managing and manipulating data in a variety of applications.
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: set it up as a source, choose a destination among 50 available off the shelf, and define which data you want to transfer and how frequently.
The most prominent ETL tools to extract data include: Airbyte, Fivetran, StitchData, Matillion, and Talend Data Integration. These ETL and ELT tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.
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.