Top ETL Tools for Excel File Integration to follow in 2024

TL;DR

The most prominent ETL and ELT tools to transfer data from Excel File include:

These ETL and ELT tools help in extracting data from Excel File 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 are Excel ETL Tools?

Excel ETL tools are software applications that extract data from Excel files (.xlsx, .xls, .csv), transform it, and load it into target systems like databases or data warehouses. For example, Airbyte can take sales data from multiple Excel files, standardize date formats and currencies, and then load it into an SQL database for analysis.

3 Common Use Cases for Excel ETL Tools

Financial Data Migration

Banks and financial firms can use Excel ETL tools to move transaction data from Excel reports into centralized databases. The tools automatically standardize currency formats, validate transaction codes, and ensure regulatory compliance during the transfer.

Sales Report Integration

Retail companies can consolidate daily sales reports from multiple stores stored in Excel sheets into a data warehouse. ETL tools automate this process by extracting sales metrics and updating dashboards with the latest data.

HR Data Consolidation

HR departments migrate employee records from Excel-based tracking sheets into HRIS systems. ETL tools map employee IDs, standardize job titles and departments, and validate data integrity before loading into the HR database.

Criterias to select the right Excel File 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 Excel File 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.

Top 10 Excel File ETL tools

Here are the top Excel File ETL tools based on their popularity and the criteria listed above:

1. Airbyte

An open-source data integration platform that supports Excel file ingestion through local files or cloud storage (like S3, GCS). It normalizes Excel data and loads it into databases, data warehouses, and lakes using pre-built connectors.

Deployment Options: Self-hosted and Cloud

Platform Type: Open Source & Cloud

Key Features:

• Custom transformations using dbt for Excel data normalization
• Automated schema mapping and error handling for Excel files
• Incremental syncs with configurable scheduling

2. Fivetran

A fully-managed ETL platform that extracts Excel data from cloud storage locations like SharePoint, Google Drive, or S3. It maintains referential integrity and automatically adapts to schema changes in Excel files.

Deployment Options: Cloud only

Platform Type: Commercial SaaS

Key Features:

• Pipeline automation
• Built-in data quality monitoring
• Historical data backfill capabilities

Here are more critical insights on the key differentiations between Airbyte and Fivetran

3. Stitch Data

Stitch is a cloud-based platform for ETL that was initially built on top of the open-source ETL tool Singer.io. More than 3,000 companies use it.

Stitch was acquired by Talend, which was acquired by the private equity firm Thoma Bravo, and then by Qlik. These successive acquisitions decreased market interest in the Singer.io open-source community, making most of their open-source data connectors obsolete. Only their top 30 connectors continue to be  maintained by the open-source community.

What's unique about Stitch?

Given the lack of quality and reliability in their connectors, and poor support, Stitch has adopted a low-cost approach.

Here are more insights on the differentiations between Airbyte and Stitch, and between Fivetran and Stitch.

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

9. Rivery

Rivery is another cloud-based ELT solution. Founded in 2018, it presents a verticalized solution by providing built-in data transformation, orchestration and activation capabilities. Rivery offers 150+ connectors, so a lot less than Airbyte. Its pricing approach is usage-based with Rivery pricing unit that are a proxy for platform usage. The pricing unit depends on the connectors you sync from, which makes it hard to estimate.

10. HevoData

HevoData is another cloud-based ELT solution. Even if it was founded in 2017, it only supports 150 integrations, so a lot less than Airbyte. HevoData provides built-in data transformation capabilities, allowing users to apply transformations, mappings, and enrichments to the data before it reaches the destination. Hevo also provides data activation capabilities by syncing data back to the APIs.

All those ETL tools are not specific to Excel File, you might also find some other specific data loader for Excel File data. But you will most likely not want to be loading data from only Excel File in your data stores.

Which data can you extract from Excel File?

The Excel File provides access to a wide range of data types, including:  
• Workbook data: This includes information about the workbook itself, such as its name, author, and creation date.  
• Worksheet data: This includes data about individual worksheets within the workbook, such as their names, positions, and formatting.  
• Cell data: This includes information about individual cells within the worksheets, such as their values, formulas, and formatting.  
• Chart data: This includes data about any charts that are included in the workbook, such as their types, data sources, and formatting.  
• Pivot table data: This includes information about any pivot tables that are included in the workbook, such as their data sources, fields, and formatting.
• Macro data: This includes information about any macros that are included in the workbook, such as their names, code, and security settings.  

Overall, the Excel File's API provides developers with a comprehensive set of tools for accessing and manipulating data within Excel workbooks, making it a powerful tool for data analysis and management.

Why Not Use Excel as an ETL Tool?

While Excel's Power Query offers basic ETL capabilities like data extraction, transformation, and loading to other worksheets, it falls short of enterprise-scale ETL. Excel hits memory limits with large datasets, lacks proper version control for transformations, and can't handle concurrent users effectively. For production ETL pipelines, Excel's limited automation options and absence of robust error handling make it risky. Besides, scheduling regular ETL jobs and maintaining audit trails - critical requirements for data engineering - are not natively supported in Excel.

How to start pulling data in minutes from Excel File

If you decide to test Airbyte, you can start analyzing your Excel File data within minutes in three easy steps:

Step 1: Set up Excel File as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Excel File" source connector and select "Create new connection."
3. In the "Connection Configuration" page, enter a name for your connection and select the version of Excel you are using.
4. Click on "Add Credential" and enter the path to your Excel file in the "File Path" field.
5. If your Excel file is password-protected, enter the password in the "Password" field.
6. Click on "Test" to ensure that the connection is successful.
7. Once the connection is successful, click on "Create Connection" to save your settings.
8. You can now use this connection to extract data from your Excel file and integrate it with other data sources on Airbyte.

Step 2: Set up a destination for your extracted Excel File data

Choose from one of 50+ destinations where you want to import data from your Excel File source. This can be a cloud data warehouse, data lake, database, cloud storage, or any other supported Airbyte destination.

Step 3: Configure the Excel File 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 Excel File 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 Excel File ETL and how to best do it.

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