Microsoft SQL Server ETL: 10 Best Tools [Both Free and Paid]

A modern ETL solution that is designed and made for today’s real-time data environment can give you an advantage over your competition. The SQL Server ETL (Extraction, Transformation, and Loading) process is especially useful when there is no consistency in the data coming from the source systems. Efficient ETL SQL Server procedures ensure seamless data integration and maintenance within the relational database management system.

Many organizations rely on SQL ETL tools to streamline their data migration and consolidation efforts. Microsoft SQL Server ETL tools can perform faster by ensuring the accuracy of data. In this blog, we will cover the best ETL tools for SQL Server that can gracefully handle the complexity that arises as the volume of data increases.

Introduction to SQL Server ETL

SQL Server ETL (Extract, Transform, Load) refers to the process of extracting data from various sources, transforming it into a usable format, and loading it into SQL Server for storage, analysis, or further processing. This process is essential for integrating data from different systems, improving data quality, and preparing data for reporting and analytics.

Key Features

Let us discuss some of its key features.

• Extraction: It is the process of gathering data from several sources, such as a database, flat files, and even cloud services.
• Transformations: Any processing that needs to be done in order to convert, clean, and enrich extracted data according to the target system’s specific needs, possibly filtering, aggregating, or applying business rules.
• Loading: Inserting the transformed data into SQL Server, where it can be stored in tables, views, or data warehouses for analysis.

Tools

• SQL Server Integration Services: This is an extremely powerful tool provided by Microsoft for ETL processes—used for the automation of data extraction, transformation, and loading into SQL Server.
• Third-Party ETL Tools: Solutions like Hevo, Pentaho, and Informatica also offer ETL capabilities for SQL Server, often providing additional features like no-code interfaces, real-time data sync, and support for a wide range of data sources.

For companies moving data from SQL Server to Redshift, selecting the right ETL tools is essential to ensure efficient and reliable data transfer, especially for large datasets.

SQL Server Integration Services (SSIS)

SSIS stands for SQL Server Integration Services. It’s a very powerful ETL tool provided by Microsoft for automating processes for extraction, transformation, and loading of data across sources and destinations. It does complex Data Integration, automation of workflow, and Data Warehousing Tasks, thus being suitable for enterprise data management. Besides, SSIS also has a drag-and-drop functionality to build and administer data workflows in a simple way.

How does it fit into the SQL Server Ecosystem?

SSIS (SQL Server Integration Services) is a core component of the SQL Server ETL ecosystem, playing a vital role in the extraction, transformation, and loading of data. It integrates seamlessly with SQL Server, allowing organizations to efficiently manage and move data between diverse sources and destinations within their SQL Server environment. SSIS enables complex data workflows, including data cleansing, aggregation, and enrichment, through its robust set of built-in transformations and tasks. By providing a flexible, scalable platform for data integration, SSIS enhances the overall data management capabilities of SQL Server, making it a key tool for building and maintaining data warehouses, data marts, and other enterprise data solutions.

Key Features of SSIS

I have highlighted some of the key features of SSIS.

• Data Integration: Integrate data from nearly any source, including databases, flat files, and XML or cloud services.
• Built-in Transformations: Provide extensive collections of pre-built, out-of-the-box transformations to meet your needs in terms of cleansing, aggregation, sorting, and merging—all allowing you to do advanced manipulation of your data.
• Workflow Automation: Automate your workflows of data using file transfers, email notifications, and execution of SQL commands, all in a way that minimizes manual intervention.
• Error Handling: It provides strong error-handling mechanisms, detailed logging, and auditing, which help in the effective tracing and management of ETL processes.

Best SQL Server ETL Tools

The ETL tools available for the SQL server database can be divided into two categories: free ETL tools and paid ETL tools. The paid tools come with a plethora of features and customizations to suit your specific requirements. The free tools essentially provide limited features related to specific use cases or requirements. You may explore these and find out which one works best for you.

Paid SQL Server ETL Tools

• Hevo Data
• Informatica PowerCenter
• Striim
• Pentaho
• IBM InfoSphere DataStage
• Oracle GoldenGate
• Qlik Replicate
• Fivetran
• Azure Data Factory

1. Hevo Data

Hevo allows you to replicate data in near real-time from 150+ sources to the destination of your choice including Snowflake, BigQuery, Redshift, Databricks, and Firebolt, without writing a single line of code.

For the rare times things do go wrong, Hevo ensures zero data loss. To find the root cause of an issue, Hevo also lets you monitor your workflow so that you can address the issue before it derails the entire workflow. Add 24*7 customer support to the list, and you get a reliable tool that puts you at the wheel with greater visibility. Check Hevo’s in-depth documentation to learn more.

And Hevo has a simple, transparent pricing model. Hevo has 3 usage-based pricing plans starting with a free tier, where you can ingest up to 1 million records.

Get Started with Hevo for Free

Hevo was the most mature Extract and Load solution available, along with Fivetran and Stitch but it had better customer service and attractive pricing. Switching to a Modern Data Stack with Hevo as our go-to pipeline solution has allowed us to boost team collaboration and improve data reliability, and with that, the trust of our stakeholders on the data we serve.

– Juan Ramos, Analytics Engineer, Ebury

Check out how Hevo empowered Ebury to build reliable data products here.

2. Informatica PowerCenter

Informatica PowerCenter is an enterprise-class data integration solution and data management system. You can use it to extract data from a source transforming it based on business requirements and loading it into a SQL Server. PowerCenter offers a vast array of connectors for both on-premise data sources or cloud services such as Redshift, Snowflake, S3, RDS, etc. 

Key Features

• Guided development wizards that automate manual tasks.
• A massively scalable parallel data integration architecture.
• Hundreds of connectors for most of the cloud offerings and on-premise sources.
• A Service-Oriented Architecture (SOA).
• A central repository service that contains all the instructions to extract, transform, and load data to MS SQL Server targets.
• A services hub gateway that exposes all the primary functionality of the product to external clients through web services and an easy-to-use UI.
• Tight integration with messaging systems.
• A highly scalable concurrent data processing system.
• Real-time change data capture that allows you to track the time, table, and the user who makes the changes.

Pricing

Informatica PowerCenter basic plan starts at $2,000/month. There is also a free fully featured 30-day trial.

3. Striim

Striim is an enterprise-grade real-time streaming data integration and operational intelligence platform. Striim’s end-to-end data integration platform uniquely combines both streaming integration and streaming intelligence in a single platform. Microsoft SQL Server users can use Striim to ingest high speed streaming data from a variety of sources which include minimal-impact change data capture from enterprise databases, log files, messaging systems, IoT sensors, et al. in milliseconds.

While the data is in transit, it’s easy to filter, transform, aggregate, and enrich it at speed to deliver it in a consumable format therefore enabling users to make operational decisions based on time-sensitive data. When deeper insights are needed, you can use Striim to correlate streaming information, detect anomalies, and identify interesting events in patterns while the data is in motion. Striim solutions can be built rapidly without coding skills so you can immediately focus on better understanding your customers and growing your business.

Key Features

• Change Data Capture from multiple databases and target support for Microsoft SQL Server.
• Multiple log parsers for shipping log data to SQL Server in real-time.
• In-memory transformations for IoT in real-time at the edge reduces the volume of data sent to SQL Server.
• Supports high volumes of data with enterprise-grade access control, security, failover, redundancy, and recovery.
• Replication verification using a built-in delivery validation solution.
• Enhanced analytics with continuous data movement and in-flight processing. 
• One of the best ETL tools for edge processing IoT sensor data.
• Stream analytics and visualization.
• A distributed architecture which helps with single point of failure risks so that when one node fails another one takes over immediately. This ensures that you have a highly available ETL pipeline and that you can have unlimited scaling as your data needs increase.
• Built-in delivery validation that uses checkpointing mechanisms to ensure that everything is processed only once without repeating the data or dropping the data.

Pricing

You can request a free 30-minute technical demo of the platform after which you can upgrade to a pay-by-the-month or an annual plan. Striim does not publicly disclose its pricing structure. Instead they offer custom features based on your needs and use case.

4. Pentaho (Kettle)

Pentaho is a simple, powerful ETL tool that can ETL your data to Microsoft SQL Server. Using Pentaho, you can perform analysis on Microsoft SQL Server data without the headache of writing and maintaining ETL scripts. Many organizations use Pentaho to move billions of records every day from SaaS applications and databases into their data warehouses, making them available for everyone in their dashboarding tools.

Using Pentaho, developers can set the replication frequency, whether batch or incremental, from databases like PostgreSQL and MySQL to SaaS tools like Salesforce and SAP. This data can be replicated to Microsoft SQL Server based on how often you want jobs to run, from every 24 hours down to every minute.

Key Features

• Pentaho is totally self-serve; there’s no relationship with account managers and no customer success representatives are needed.
• It is very simple to set up an ETL process.
• You can manage your entire ETL system from the Pentaho dashboard.
• Numerous integrations covering most top services.
• Documentation is to the point and very helpful.

Pricing

There is a free tier that will allow you to test out the service thoroughly. The Standard plan starts out at $100 per month to process 5 million rows and you can easily adjust your plan as you grow. For mission-critical applications you can contact their sales reps to get custom integrations, custom quotas, priority support, and service level agreements to meet your requirements.

5. IBM InfoSphere DataStage

If you have multiple targets and source systems, you can use InfoSphere Information Server as your primary corporate data integration platform. Infosphere DataStage is a cross-departmental integration platform for extracting, transforming and loading data. Organizations use DataStage to integrate data from a wide spectrum of data sources e.g. Oracle database, spreadsheets, MySQL, etc.

Key Features

• Easy to implement and connect to various external data sources.
• A wide variety of connectors.
• Ability to ETL data from any source system to any destination.
• Support for Visual Basic, and supports the C language.
• It can process big data and unstructured data.
• ETL flexibility without coding.
• MPP Processing Engine.
• Metadata management capabilities.
• Extreme data volume processing.
• Ability to perform data profiling, data cleansing, and metadata management.

6. Oracle GoldenGate

Oracle GoldenGate is one of the most comprehensive ETL tools that provides high-speed, low impact, real-time data integration and replication in disparate IT environments. Using GoldenGate, you can easily replicate, filter, and transform transactional data from popular database systems into SQL Server. GoldenGate is designed for real-time, change data capture, routing, and delivery.

Key Features

• High-performance ETL processing.
• Simplified configuration and management.
• Easy to analyze problems when they occur.
• Log-based change data capture, distribution, transformation, and delivery
• Support for popular databases and operating systems.
• Bidirectional replication.
• Reliable data delivery and fast recovery after interruptions.

Pricing

Oracle GoldenGate for non Oracle databases starts from $1,750.00 – $17,500.00.

7. Qlik Replicate

Qlik Replicate (formerly Attunity Replicate) provides real-time insights into enterprise data. The platform is enabling hundreds of enterprises to accelerate data replication, ingestion and streaming across a broad range of sources and targets including SQL Server. Qlik Replicate moves your data easily, securely and efficiently, on-premise and in the cloud.

Key Features

• Simplified big data ingestion into SQL Server from thousands of sources.
• Ability to automatically generate target schemas based on source metadata.
• Low latency ETL processing with parallel threading.
• Uses change data capture process (CDC) to maintain true real-time analytics with less overhead.

Pricing

Qlik does not publicly disclose its pricing. To purchase Qlick, you first need to have a conversation with one of their sales representatives.

8. Fivetran

Fivetran stands out as a cloud-based data integration platform designed to simplify the process of consolidating data into Microsoft SQL Server. It achieves this by automating ETL tasks, thus minimizing manual effort and streamlining workflows.

A noteworthy aspect of Fivetran is its capability to automatically extract data from more than 150 different sources, spanning from popular marketing tools to Customer Relationship Management (CRM) systems and databases. This data is then efficiently replicated in near real-time to the designated SQL database.

Moreover, users can leverage SQL-based transformations to refine and manipulate the data as needed before it reaches its final destination. Fivetran ensures data security and compliance with industry regulations such as GDPR and HIPAA, offering peace of mind to users.

Key Features

• Provides automated Extract, Transform, Load (ETL) processes.
• Provides seamless integration to with SQL Server with pre-built connectors.
• Provides advanced encryption for data security.

Pricing

The pricing model of Fivetran is structured based on the number of connectors utilized and the volume of data processed.

9. Azure Data Factory

Azure Data Factory stands as Microsoft’s fully managed and serverless solution for data integration. Leveraging Azure’s extensive library of built-in connectors, users can effortlessly integrate their data without delving into intricate coding processes. Notably, Azure Data Factory encompasses both ETL and ELT functionalities, along with native support for Git and Continuous Integration/Continuous Deployment (CI/CD).

A notable advantage of Azure Data Factory is its ability to seamlessly rehost or extend on-premise SQL Server Integration Services (SSIS), making it an attractive option for users seeking a hybrid data solution.

Key Features:

• Provides seamless ETL processes without the need for extensive coding.
• Autonomous ETL features and streamlines data integration tasks.

Pricing

Microsoft provides a complimentary $200 credit, valid for 30 days, allowing users to explore the platform’s capabilities. For users requiring additional resources beyond the free allocation, Azure Data Factory offers a pay-as-you-go pricing model tailored to individual needs.

Free SQL Server ETL Tools

1. Microsoft SQL Server Integration Services

SQL Server Integration Services or SSIS is a powerful tool for performing various ETL-like functions between analogous and dissimilar sources of data. Many organizations cite that the number one reason why they use SSIS is that it provides an easy way to create data transformations. SSIS comes as a built-in feature in SQL Server Standard, Enterprise, Express, and Workgroup editions so that you don’t have to spend extra cash on third-party ETL tools.

You can use the SQL Server Integration Services to ingest data into your SQL Server data warehouse in varied ways such as a bulk load or incremental loads thanks to the use of Slowly Changing Dimension transformation tasks. 

Key Features

• Easy connection configuration.
• Powerful wizard for data mapping.
• Native exception handling.
• User-friendly interface.
• Easy to learn.
• The SSIS package can be deployed via Visual Studio.
• High data load speeds.
• Many data processing modes.
• Requires relatively little maintenance.

Pricing

SSIS is provided without charge seeing that it is already integrated into SQL Server Licenses.

2. Talend Open Studio

Talend Open Studio is one of the most innovative and powerful Open Source data integration solutions on the market today. It is able to meet the data integration needs of many types of organizations. Open Studio supports ETL (Extract, Transform, Load) and can be deployed on-premise as well as in a SaaS model. Talend Open Studio or TOS, provides an intuitive graphical user interface that you can use to drag and drop components and connect them to create and run ETL pipelines. TOS will generate the Java code for the job automatically and you need not write a single line of code.

You can use Talend Open Studio to connect your SQL Server warehouse to 900+ data sources such as RDBMS, Google Sheets, SaaS applications, etc.

Key Features

• The tool is completely free
• Business modeling
• Graphical development
• Metadata-driven design and execution
• Real-time debugging
• Robust execution

Pricing

Talend Open Studio is available for free download and is licensed under an open-source license – Apache License 2.0.

3. Apache Nifi

Apache Nifi aims to make data analytics teams more productive. Apache Nifi’s ETL solution lets analysts build data warehouses without internal IT resources or knowledge of complex scripting languages.

Apache Nifi is your autopilot for automating ETL workflows. Data teams can easily set up pipelines using Apache Nifi to extract data from any source and load clean and structured data into SQL Server. Apache Nifi monitors and maintains data pipelines, reducing engineering’s need for constant maintenance. They provide an interactive data wrangler which will let you control how your data is transformed, without writing any code. Apache Nifi will connect to your SQL Server database to create a high performance data warehouse in minutes. Apache Nifi supports a wide variety of integrations meaning you can connect to sources such as Salesforce, MySQL, Amazon RDS, and Google Analytics.

Key Features

• Seamless integration with Microsoft SQL Server.
• Complex transformations, no coding. Apache Nifi data wrangler makes it easy to define any kind of data transformation to the source data.
• Multithreading feature to execute large jobs faster.
• Data splitting feature that reduces processing time.
• Capable of masking fields to protect sensitive data.
• A vibrant user community that shares information about the product openly.

Pricing

The Apache Nifi is provided under the open-source Apache License 2.0.

What are the Data Extraction Techniques in SQL Server ETL?

The different techniques of SQL Server Data Extraction are explained below:

• Full Extraction: In this technique, it extracts the entire dataset from the source system every time the ETL runs. It is a simple technique and thus may become slow and resource-intensive for huge volume data.
• Incremental Extraction: This approach extracts only data that has changed since the last ETL Process. It’s efficient and reduces the load on source and ETL process; thus, this technique can be used in large volume datasets.
• Change Data Capture (CDC): It uses SQL Server’s Change Data Capture functionality to monitor and capture all of the changes to your data. CDC is really good at picking up inserts, updates, and deletes in near real-time.
• Log-Based Extraction: This method involves reading changes directly in the database transaction logs. The technique is non-intrusive and captures the changes with very minimal impacts on source system performance.

Common Challenges and Solutions in SQL Server ETL

Challenges	Solutions
Inconsistent, incomplete, or inaccurate data can affect the quality of the ETL process.	Implement data validation and cleansing during the ETL process to identify and correct errors.
Large volumes of data or complex transformations can lead to slow ETL performance and system resource contention.	Optimize ETL performance by using efficient data extraction techniques, leveraging SSIS’s parallel processing capabilities, and indexing source tables.
Errors during ETL processes can disrupt data flows and require effective handling and recovery mechanisms.	Implement robust error handling and logging within SSIS packages to capture and manage errors.
Ensuring data security and compliance with regulations during ETL processes can be challenging.	Apply encryption for data in transit and at rest, use secure connections, and adhere to data governance policies.
Regular maintenance and monitoring of ETL processes are required to ensure ongoing reliability and performance.	Use SQL Server’s built-in monitoring tools, such as SQL Server Management Studio (SSMS) and SQL Server Agent, to schedule and monitor ETL jobs.

Microsoft SQL Server – Relational DB

Microsoft SQL Server is a relational database management system that supports a wide variety of applications in corporate IT environments — from transaction processing to business intelligence to analytics.

As the name suggests, SQL Server is built on top of SQL, a language that database administrators and IT professionals use to manage and search databases. Microsoft SQL Server competes primarily against Oracle Database and IBM’s DB2 in the relational database management field.

Within SQL Server, Microsoft also includes a variety of data management, business intelligence, and analytics tools like R services, Machine Learning services, and SQL Server analysis services. Microsoft also offers different editions of SQL Server to fit different organization sizes and business needs. Its editions include:

1. A free, full-featured Developer Edition for database development and testing.
2. A free Express Edition for small databases with 10 gigabytes of storage capacity.
3. A Standard Edition with limited features and limits to the number of configurable processor cores and memory sizes.
4. A full-featured Enterprise Edition.

Future Trend  in SQL Server ETL 

• Increased integration of SQL Server ETL processes with cloud platforms like Azure, AWS, and Google Cloud for increased scalability, flexibility, and decreased costs—making for a more dynamic and hybrid data environment.
• Increased focus on real-time data processing and streaming ETL for higher decision-making abilities and operational efficiencies, analyzing and acting on data as it arrives.
• It will be possible to carry out advanced data transformation and artificial intelligence that will facilitate predictive analytics and data enrichment, thereby improving the capability of complex data processing, anomaly detection, and automation of data quality tasks.

Conclusion

There are a plethora of SQL Server ETL tools available in the market and one may suit you better than the other depending on your particular use case, data sources, existing applications, etc. If you wish to implement this ETL manually, it will consume your time & resources and is error-prone. Moreover, you need a full working knowledge of the backend tools to successfully implement the in-house data transfer mechanism. So it’s optimal to depend on an ETL tool like Hevo! You can also schedule a personalized demo with us to learn more about SQL Server Integration.

FAQs about SQL Server ETL