Top ETL Tools

Top 10 ETL Tools for Data Integration

Top 5 SQL Server Data Tools for 2024

March 12, 2024

Microsoft SQL Server remains a popular choice for businesses seeking a robust and reliable relational database management system. Its vast array of features and capabilities empowers you to store, retrieve, and manipulate data efficiently. There are several powerful SQL Server data tools available in the market to enhance the management and analysis of your data.

It's crucial for your businesses to have advanced tools to handle large volumes of data. In this blog, you will explore the top five SQL Server data tools for the year 2024, highlighting their key features and benefits.

Top 5 SQL Server Data Tools

Here are some of the most popular SQL server data tools, along with their key features:

SQL Server Management Studio (SSMS)

SQL Server Management Studio (SSMS) is a comprehensive, integrated environment developed by Microsoft for managing SQL Server databases. It offers a graphical user interface that allows you to interact with SQL Server instances and perform various tasks. It enables you to write SQL queries of any complexity with high efficiency.

Here's an overview of its key features:

Query Editor: SSMS includes a powerful query editor that enables you to write and execute Transact-SQL (T-SQL) queries against SQL Server databases. It provides syntax highlighting and debugging capabilities to help you write SQL queries with ease.

Object Explorer: Object Explorer in SSMS offers a hierarchical user interface for viewing and managing objects within each SQL Server instance. It displays instance objects in a tabular format and enables you to search for specific objects.

Template Explorer: In SSMS, template scripts are available to assist in creating objects such as databases, tables, views, indexes, triggers, and functions. These scripts contain parameters that can be customized to tailor the code to specific requirements.

Integration with Other Tools: It integrates well with other SQL Server-related tools and services. For example, you can integrate SSMS with SQL Server Reporting Services (SSRS) for creating and managing reports.

dbForge Studio

dbForge Studio is a comprehensive, integrated development environment (IDE) designed for SQL Server database development, management, and administration. The Source Control functionality incorporated into dbForge Studio enables you to maintain database integrity, enhance team collaboration, and streamline database deployment processes more effectively.

Here's an overview of its key features:

Data Import and Export: With dbForge Studio, you can easily import and export data to and from SQL Server databases. It supports various data formats, including Excel, CSV, XML, and more. You can customize import and export settings and automate data transfer tasks via the command line.

SQL Coding Assistance: The IDE provides advanced code completion, code snippets, and syntax highlighting for writing SQL queries and scripts. It helps improve productivity and reduces coding errors by suggesting code elements, keywords, and objects as you type.

Query Profiler: dbForge offers a Query Profiler tool designed to help you analyze and optimize the performance of queries in SQL Server databases. It generates profiling results that provide detailed statistics about executed queries. This allows you to identify and address slow queries and troubleshoot performance issues.

Database Administration: Security Manager in dbForge Studio is a powerful SQL Server administration tool designed to protect your data and streamline admin tasks. It lets you define and manage user roles, permissions, and access controls to guarantee that only authorized individuals can access sensitive data.

MySQL Workbench

MySQL Workbench is a unified visual database design and administration tool developed by Oracle Corporation. It provides a comprehensive set of features for managing MySQL databases. Additionally, MySQL Workbench provides a user-friendly solution for migrating tables, objects, and data from Microsoft SQL Server and other relational database management systems (RDBMS) to MySQL.

Here's an overview of its key features:

Database Administration: MySQL Workbench provides a visual console to easily administer MySQL environments and gain better visibility into databases. You can use the visual tools to configure servers, manage users, and perform backups and recoveries.

Visual Performance Dashboard: It includes performance reports that offer detailed insights into the performance of MySQL applications. These reports provide valuable information about IO hotspots, high-cost SQL statements, and other performance-related metrics. You can use this information to identify areas that require optimization.

Data Modeling: MySQL Workbench allows you to create, edit, and manage database models using entity-relationship diagrams (ERDs). It supports forward and reverse engineering capabilities, enabling you to generate SQL scripts from existing databases or vice versa.

SQL Development: You can write SQL queries directly within the integrated SQL Editor. This allows you to create, edit, and execute SQL queries conveniently within the Workbench environment. 

Aqua Data Studio

Aqua Data Studio is a versatile universal database IDE. It caters to various database platforms, including relational, NoSQL, and cloud-based databases. This powerful tool offers a wide range of features designed to streamline SQL Server management tasks and enhance productivity. 

Here's an overview of its key features:

Visual Query Builder: It helps you construct complex database queries with ease. Query builders help minimize errors by automatically generating SQL code based on user inputs. This reduces the possibility of syntax errors and logical mistakes.

Table Data Editor: It provides a Table Data Editor feature that allows you to make changes to the result set of an executed query on a table using a convenient graphical interface. This makes it easy to modify data and perform actions such as adding or deleting rows.

Visual Data Analytics: In Aqua Data Studio, the Visual Analytics feature empowers you to transform query results into visually engaging representations. You can create interactive dashboards by effortlessly dragging in visualizations from multiple worksheets. 

Cross-Platform Compatibility: Aqua Data Studio is compatible with Windows, macOS, and Linux platforms, providing flexibility across different operating systems.

Toad for SQL Server

Toad for SQL Server is a comprehensive database management tool designed to streamline SQL Server development and administration tasks. It complements Microsoft tools by addressing core SQL Server challenges, allowing you to manage multiple databases.

Here's an overview of its key features:

SQL Optimizer: The SQL Optimizer in Toad facilitates application performance tuning by automating query rewrites and optimization processes. With this functionality, you can effortlessly improve the performance of SQL queries.

Security management: Toad offers a comprehensive security management feature that enables you to manage and replicate security settings for all users across multiple servers. With this, you can effortlessly build and execute security-related scripts to enforce consistent security measures.

Schema Comparison and Synchronization: Toad enables you to compare and synchronize database schemas between different environments. This promotes consistency and integrity across databases.

Customized Reports: Toad enables you to create customized reports for administration and development. These reports can be exported in versatile formats, including Microsoft Excel, XML, Microsoft Word, and Adobe Acrobat. This ensures compatibility and accessibility across different platforms and applications.

Simplify SQL Server Data Management with Airbyte

Although Microsoft SQL Server is considered one of the more user-friendly options available, it still requires a high level of expertise, particularly when migrating SQL Server data to a new destination. This is where Airbyte, a data integration and replication platform, can greatly assist. 

With Airbyte, you can easily transfer data from/into SQL Server using low-code or no-code data pipelines. Its intuitive interface and pre-built connectors streamline the process, allowing you to set up and execute data replications without extensive SQL knowledge or manual scripting. This not only reduces the complexity of data migration but also accelerates analysis.

Here are the key features of Airbyte:

Connectors: Airbyte offers a wide catalog of over 350 pre-built connectors, including Microsoft SQL Server (MSSQL). It allows you to consolidate data from multiple sources and bring it all together into your target system, creating a unified view for easy analysis. 

Customization: Airbyte offers the Connector Development Kit (CDK) feature, which empowers you to develop custom connectors and construct data pipelines connecting your preferred source and destination systems. With Airbyte's CDK, you can create a no-code connector in less than ten minutes or develop a low-code connector in under 30 minutes.

Change Data Capture (CDC): The Change Data Capture (CDC) feature in Airbyte allows you to capture and track modifications or changes made to your dataset directly at the source. This captured data can then be seamlessly migrated to your destination. When configuring the data pipeline, you have the option to specify the incremental sync frequency, ensuring that only the updated or modified data is transferred.

Wrapping Up

This article explored the top five SQL Server data tools, delving into their key features and functionalities. Each tool offers unique capabilities to enhance SQL Server data management and analysis. 

Check out our latest article on SQL Server ETL tools, where we delve into the top five solutions. If you're seeking an ideal data consolidation tool for Microsoft SQL Server.

However, if you are looking for an ideal solution to consolidate data in Microsoft SQL Server, we recommend using Airbyte. With its user-friendly interface and powerful capabilities, Airbyte simplifies the whole integration process. Explore its unique features and enhance your analysis by signing up for Airbyte today!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

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TL;DR

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

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • These ETL and ELT tools help in extracting data from 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 ETL?

    ETL (Extract, Transform, Load) is a process used to extract data from one or more data sources, transform the data to fit a desired format or structure, and then load the transformed data into a target database or data warehouse. ETL is typically used for batch processing and is most commonly associated with traditional data warehouses.

    What is ELT?

    More recently, ETL has been replaced by ELT (Extract, Load, Transform). ELT Tool is a variation of ETL one that automatically pulls data from even more heterogeneous data sources, loads that data into the target data repository - databases, data warehouses or data lakes - and then performs data transformations at the destination level. ELT provides significant benefits over ETL, such as:

    • Faster processing times and loading speed
    • Better scalability at a lower cost
    • Support of more data sources (including Cloud apps), and of unstructured data
    • Ability to have no-code data pipelines
    • More flexibility and autonomy for data analysts with lower maintenance
    • Better data integrity and reliability, easier identification of data inconsistencies
    • Support of many more automations, including automatic schema change migration

    For simplicity, we will only use ETL as a reference to all data integration tools, ETL and ELT included, to integrate data from .

    How data integration from to a data warehouse can help

    Companies might do ETL for several reasons:

    1. Business intelligence: data may need to be loaded into a data warehouse for analysis, reporting, and business intelligence purposes.
    2. Data Consolidation: Companies may need to consolidate data with other systems or applications to gain a more comprehensive view of their business operations
    3. Compliance: Certain industries may have specific data retention or compliance requirements, which may necessitate extracting data for archiving purposes.

    Overall, ETL from 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 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 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 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 ETL tools

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

    1. Airbyte

    Airbyte is the leading open-source ELT platform, created in July 2020. Airbyte offers the largest catalog of data connectors—350 and growing—and has 40,000 data engineers using it to transfer data, syncing several PBs per month, as of June 2023. Major users include brands such as Siemens, Calendly, Angellist, and more. Airbyte integrates with dbt for its data transformation, and Airflow/Prefect/Dagster for orchestration. It is also known for its easy-to-use user interface, and has an API and Terraform Provider available.

    What's unique about Airbyte?

    Their ambition is to commoditize data integration by addressing the long tail of connectors through their growing contributor community. All Airbyte connectors are open-source which makes them very easy to edit. Airbyte also provides a Connector Development Kit to build new connectors from scratch in less than 30 minutes, and a no-code connector builder UI that lets you build one in less than 10 minutes without help from any technical person or any local development environment required.. 

    Airbyte also provides stream-level control and visibility. If a sync fails because of a stream, you can relaunch that stream only. This gives you great visibility and control over your data. 

    Data professionals can either deploy and self-host Airbyte Open Source, or leverage the cloud-hosted solution Airbyte Cloud where the new pricing model distinguishes databases from APIs and files. Airbyte offers a 99% SLA on Generally Available data pipelines tools, and a 99.9% SLA on the platform.

    2. Fivetran

    Fivetran is a closed-source, managed ELT service that was created in 2012. Fivetran has about 300 data connectors and over 5,000 customers.

    Fivetran offers some ability to edit current connectors and create new ones with Fivetran Functions, but doesn't offer as much flexibility as an open-source tool would.

    What's unique about Fivetran? 

    Being the first ELT solution in the market, they are considered a proven and reliable choice. However, Fivetran charges on 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 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.

    Other potential services

    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.

    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.

    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.

    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.

    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.

    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.

    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.

    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. 

    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. 

    Meltano

    Meltano is an open-source orchestrator dedicated to data integration, spined off from Gitlab on top of Singer’s taps and targets. Since 2019, they have been iterating on several approaches. Meltano distinguishes itself with its focus on DataOps and the CLI interface. They offer a SDK to build connectors, but it requires engineering skills and more time to build than Airbyte’s CDK. Meltano doesn’t invest in maintaining the connectors and leave it to the Singer community, and thus doesn’t provide support package with any SLA. 

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

    Which data can you extract from ?

    How to start pulling data in minutes from

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

    Step 1: Set up as a source connector

    Step 2: Set up a destination for your extracted data

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

    Step 3: Configure the 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 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 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:

    flag icon
    Easily address your data movement needs with Airbyte Cloud
    Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
    Get started with Airbyte for free
    high five icon
    Talk to a data infrastructure expert
    Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
    Talk to sales
    stars sparkling
    Improve your data infrastructure knowledge
    Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
    Subscribe to newsletter

    Build powerful data pipelines seamlessly with Airbyte

    Get to know why Airbyte is the best SQL Server Data Tools

    Sync data from SQL Server Data Tools to 300+ other data platforms using Airbyte

    Try a 14-day free trial
    No card required.

    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.

    What is ?

    What data can you extract from ?

    How do I transfer data from ?

    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.

    What are top ETL tools to extract data from ?

    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.