The 10 Best Tools for Microsoft SQL ETL in 2024

Businesses need to integrate data before they can use it to inform their strategic decisions. It is a process that involves consolidating information from various sources, transforming it into a unified format, and loading it into a centralized repository. To streamline and accelerate this process, organizations leverage ETL tools and solutions. A common example is using SQL ETL tools to combine data into a Microsoft SQL Server database.

However, with so many tools and solutions to choose from, organizations must do their due diligence to ensure that their SQL ETL solution of choice best satisfies their needs. So, in this article we will explore some of the most capable SQL ETL tools for data integration. But first, let’s get some basics out of the way.

What is Microsoft SQL Server?

Microsoft SQL Server is a relational database management system (RDBMS). It’s one of the most popular databases used by businesses of all sizes across industries. Its popularity stems from its ability to efficiently handle structured data, providing a secure and scalable environment for data storage and retrieval.

SQL Server’s comprehensive suite of tools and services caters to the diverse needs of businesses. Its extensibility is evident through components, such as SQL Server Integration Services (SSIS) for ETL, SQL Server Reporting Services (SSRS) for creating and managing reports, SQL Server Analysis Service (SSAS) for analytical data models, and so on.

While SSIS is Microsoft’s own ETL service, it’s not the only player in the data integration landscape that enables users to implement ETL in SQL Server, as we’ll see later in the article.

ETL in SQL

ETL SQL scripts allow developers to facilitate the data movement and transformation between various systems. In the data extraction phase, developers retrieve data from source systems such as databases, flat files, APIs, or other data repositories.

Example ETL SQL code to obtain data:

The transform phase is greatly facilitated by SQL’s rich set of data manipulation and transformation functions, allowing developers to clean, aggregate, and restructure the extracted data to meet the desired format and business logic. Additionally, they can join tables, filter data, and perform calculations. The goal is to prepare the data for optimal loading into the target system.

Here’s an example of ETL SQL code to transform data:

In the Load phase, ETL SQL scripts enable data professionals to insert, update, or merge the transformed data into the destination tables.

Example ETL SQL code to load data:

While this manual approach provides developers with a flexible solution for orchestrating the ETL workflow in SQL environment, real world scenarios call for advanced SQL ETL tools and technologies to achieve efficient and scalable data integration.

The Need for Microsoft SQL ETL Tools

Traditional data integration methods involve extracting information from various sources, transforming it to meet specific business requirements, and loading the refined data into the target database, such as a SQL Server database, using ETL SQL scripts.

The demand for SQL ETL tools arises from the need for efficient data management processes within organizations. Businesses need a more streamlined and user-friendly environment to manage their entire ETL workflows. As such, the traditional means of extracting, transforming, and loading data into a centralized repository for decision-making are no longer capable of delivering the requisite time-to-insight.

In recent years, there has been a notable shift towards using no-code SQL ETL tools. These tools play a pivotal role in enabling seamless integration and synchronization of data from various sources, ensuring a cohesive and accurate data ecosystem. Particularly, SQL ETL tools provide a user-friendly and intuitive platform that empowers users with diverse backgrounds to design and implement automated data pipelines effortlessly. As a result, they have become indispensable tools for businesses of all sizes.

The Best SQL ETL Tools in 2024

As businesses continue to accumulate and integrate vast amounts of data, the demand for robust and efficient tools has never been higher. In this section, we delve into the top-performing SQL ETL tools and explore their features.

Astera

Astera is an automated data management platform with powerful ETL, ELT, and change data capture (CDC) capabilities. It features a 100% no-code UI that’s incredibly user-friendly, making it simple and easy to use even for users without a technical background.

 

Whether you need to manage unstructured data, create fully automated data pipelines, build a data warehouse, manage APIs, or enable frictionless B2B communication via EDI, everything is a matter of drag-and-drop and point-and-click. Astera’s suite of products includes:

• ReportMiner to handle unstructured data extraction in bulk
• Data Pipeline Builder to integrate data via both ETL and ELT
• Data Warehouse Builder to design a custom data warehouse from scratch
• API Management to design, publish, and monitor APIs
• EDI Management to communicate with your trading partners

Astera also offers embedded data quality features and built-in connectors, enabling users to streamline ETL in SQL Server without writing a single line of code. Users can also leverage Astera’s SQL Server CDC to capture and track changes and ensure up-to-date SQL Server replication.

Talend (acquired by Qlik)

Talend is a data integration platform featuring a drag-and-drop UI and built-in connectors. It offers multiple products, such as Talend Open Studio—an open-source offering—and Talend Data Fabric. While not completely code-free, Talend’s low-code approach is still better than writing ETL SQL scripts manually to integrate data into SQL Server.

Given its recent acquisition and the fact that it requires users to have a background in Java, users seek various Talend alternatives for data integration and management.

SSIS

SSIS is Microsoft’s service for data integration and can be particularly useful in scenarios where an organization is already invested in its ecosystem. It offers seamless integration with other Microsoft products and services, such as a SQL data warehouse, SQL Server databases, Azure services, and Excel, making it a natural choice for organizations already using Microsoft technologies.

While it offers a visual interface, it can still be overwhelming for beginners, and there is a learning curve for those who are not familiar with SSIS concepts and practices. Then there’s the issue of limited support for non-Microsoft databases when compared to other ETL tools. Additionally, SSIS is not the best choice for streaming data since it’s largely optimized for batch-processing ETL.

Apache NiFi

Apache NiFi is another possible SQL ETL tool well-known for its workflow capabilities. Its focus is on processing and moving data reliably. Like other solutions, NiFi has a visual UI to design ETL flows. It offers built-in processors specifically designed for interacting with SQL Server databases. This makes it easy to establish connections, extract data, and load it into SQL Server.

Apache NiFi can be a viable choice for ETL with SQL Server given that it offers a balance between usability and visual design. However, mastering all its features requires considerable learning, especially for new users. NiFi’s primary focus is on data movement, and while it does offer basic transformation capabilities, it is not as feature rich as other dedicated ETL tools, such as Astera, for complex data transformation. This means that users will most likely need to augment NiFi with custom scripts or additional tools to transform the data as needed.

Pentaho

Pentaho is primarily a business intelligence (BI) tool, but it provides several features for data integration, including ETL. It offers a visual UI and native connectors for SQL Server, simplifying the process of extracting and loading data to and from SQL Server databases.

Pentaho supports batch processing well; however, its real-time processing capabilities might be limited compared to some specialized tools. For use cases requiring extremely low-latency data processing, additional tools may be needed, for example, integrating the platform with Apache Spark. Some advanced features and functionalities are only available in the enterprise edition of Pentaho, which requires a commercial license.

Informatica

Informatica is an enterprise-grade data management tool that offers several products and services to integrate data for BI and analytics. It also offers ETL that allows users to move data to and from several databases, including SQL Server.

Informatica is well-known for its complex UI that, in some cases, requires professional certifications to master certain modules. Additionally, its products and services have vastly different interfaces that make it challenging for users to navigate. While it does provide the ability to transform data, complex transformations consume considerable amounts of memory and computing resources. These are some reasons why consumers look for Informatica alternatives.

Azure Data Factory

Azure Data Factory (ADF) is another one of Microsoft’s ETL services. It’s a cloud ETL service for data integration and transformation. It can be integrated with SSIS, enabling users to run SSIS packages on ADF with full compatibility. And like other SQL ETL tools, Azure Data Factory also offers a visual UI.

Users report that ADF’s visual interface quickly becomes cluttered, especially when working with workflows and multiple activities simultaneously. Additionally, even though it does support incremental data loads, the setup is mostly manual and, therefore, complex.

Matillion

Matillion is another tool that can ETL data to and from a SQL Server database with its native connector. As is the case with data integration solutions these days, Matillion also offers a visual UI with drag-and-drop functionality. Given its focus on cloud data warehouses, Matillion can be a viable option for ETL tasks in cloud environments—even more so if SQL Server is hosted in a cloud environment (e.g. Azure SQL Database).

While Matillion does feature a visual design, users typically need additional training and expertise to fully utilize its capabilities. Moreover, with its focus on the cloud, its feature-set is not as optimized for on-premises settings. Finally, Matillion’s pricing is based on concurrent users and data volume, which can be expensive for smaller organizations with limited use cases. All these nuances prompt data teams to look for Matillion alternatives.

Stich

Stitch is a cloud-based ETL tool with a focus on making the data available for analytics as quickly as possible. Stitch offers a user-friendly interface and pre-built connectors for a wide range of data sources and destinations, including SQL Server. Its integrations are powered by Singer, which is an open-source standard for building data integrations. The use of Singer ensures that Stitch’s integrations are extensible and customizable, providing users with the flexibility to tailor data pipelines to their specific needs.

Stitch was acquired by Talend, which in turn was acquired by Qlik, and even though the parent company has publicly committed to supporting Stitch as an independent offering, the overall strategic direction is still unclear, prompting existing customers to consider other SQL ETL tools.

Additionally, the users have reported that Stitch’s UI is not as user-friendly when compared to other similar tools.

Integrate.io

Integrate.io is a cloud-based data integration tool offering multiple solutions including ETL, reverse ETL, and API management. Like all the MS SQL ETL tools discussed in this list, Integrate.io also features a visual, drag-and-drop based UI to set up and build data pipelines.

Integrate.io users report that the error messages are not intuitive or self-explanatory, making it difficult to understand the actual problem and, consequently, troubleshoot it. Additionally, it mostly works with cloud-based data sources, which means users cannot work with local files (excel or csv) stored on their local system.

Choosing the Right SQL ETL Tool

Given the widespread availability of different tools and platforms to ETL data to and from SQL Server, choosing the best can feel like navigating a sea of options. The key is to find a solution that best fits the company’s most immediate and long-term requirements. As such, one must ask the right questions.

For example:

• What are the specific needs and the nature of data workflows?
• Are robust, built-in transformations a must-have or a nice-to-have?
• Overall, how tech-savvy is the data team? Are the tool’s ease-of-use and flexibility important factors?
• Is scalability going to be a prohibiting factor in the future?

The fact that more and more business users, or citizen integrators, are taking charge in the data integration landscape, the “best” SQL ETL tool will ultimately be the one that:

• Caters to the business use case
• Is economical with transparent pricing
• Empowers business users with an intuitive UI
• Backed by a proactive customer support team

 

Wrap Up

Leveraging data integration tools instead of writing ETL SQL scripts to integrate data into a SQL Server database offers multiple benefits. First, they provide a visual and intuitive interface that simplifies the overall ETL process, allowing users to design and manage data workflows through a visual representation of the integration pipeline.

Second, SQL Server ETL tools typically provide advanced functionalities such as data validation, error handling, and job scheduling. Finally, these tools often support a variety of data sources and formats which further facilitates seamless integration of diverse data sets into the SQL Server database.

Do you have a unique use case and are looking for a simple yet powerful SQL ETL solution? Get in touch with one of our solutions experts today.