Top 10+ Data Warehouse Automation Software in 2024

Though data warehouse automation (DWA) increases productivity of data warehouse teams, reduces time to integrate new data sources, leads to improved data quality and increases flexibility, most data engineers still rely on manual coding in this domain. One of the reasons of this slow adoption is that it is challenging to choose the right data warehouse automation software since:

• There are 10+ DWA platforms to choose from
• Existing data warehouse needs to be connected to numerous data sources requiring careful review of integrations provided by the data warehouse automation tools
• Users need to evaluate it for ease of use.

Therefore, this article provides a comprehensive checklist to shortlist the top data warehouse automation software.  

What are the data warehouse automation software?

Above table includes all solution that we came across in this category. Below, we shortlisted 10 of them for more detailed analysis.

Shortlisting market leaders

The variety of players in the market slows down the review process. Therefore, we shortlist major actors based on 3 factors:

• The number of employees on LinkedIn: We included only vendors with more than 10 employees listed on LinkedIn. It is rare for a smaller company to offer enterprise solutions.
• Types of vendors: We categorize vendors into two groups based on their focus and scope: workload automation (WLA) and data warehouse automation (DWA). We included all DWA vendors in our listing. We selected only the top 3 workload automation software since DWA is not their core focus. We used number of B2B reviews as the basis of our selection in the WLA market. You can review our constantly updated and comprehensive list for WLA tools and evaluate top WLA software in our data-driven vendor benchmark.
• Reviews: We excluded vendors without any B2B reviews on any platform, as the lack of feedback could imply a low adoption rate of their tools. Therefore, out of 13 top vendors that you can see above, we focused on 10 with reviews.

Find more comprehensive vendor lists by:

• Checking out our data-driven and constantly updated workload automation and IT automation software lists.
• Skimming over our comprehensive benchmarks for IT automation software and workload automation tools.

10 Data warehouse automation software market leaders

Here is a detailed explanation for selected vendors listed according to total B2B numbers in descending order for each category:

The comparison table above is based on major B2B review platforms (such as G2 and TrustRadius). The vendors are listed according to their total B2B reviews (See Figure 1).

1. ActiveBatch

ActiveBatch is an enterprise workload automation and job scheduling software, providing a comprehensive platform for automating and orchestrating complex IT and business processes across diverse systems, applications, and environments. 

Pros:

• Data Integration and ETL: ActiveBatch provides a wide range of built-in connectors and integration capabilities to extract data from various sources, transform it, and load it into the data warehouse. This way, it streamlines data ingestion and preparation by offering intuitive drag-and-drop design tools.

 Cons:

• Learning curve: The most prominent comment from users was the difficulty to learn the tool at first. The users recommended to provide more detailed instructions on how each function works.¹ 

2. Redwood RunMyJobs

Redwood RunMyJobs is a comprehensive job scheduling and workload automation tool to automate and manage complex business processes, workflows, and job scheduling tasks across diverse systems and applications. It provides advanced features like dependency management, real-time monitoring, and extensive reporting and analytics capabilities. 

Check out the video to see how Redwood RunMyJobs can simplifies the creation, scheduling, and monitoring of jobs to optimize business processes and achieve reliable and timely job execution:

 Pros:

• Data integrations: Redwood offers built-in connectors to extract data from various applications and databases, such as SAP and Oracle.  
• Data handling: Redwood users express their satisfaction with transferring and handling data without any security concerns. ² 
• Reporting & BI: Redwood offers a variety of dashboards, reporting systems and BI tools, which allows employees to view all stats and deliver insights on their data warehouse operations (See Figure 3).  

 Cons:

• Time-consuming: Users complained about the time loss for converting the file format to Excel while downloading reports. ⁴ 

3. Control-M

Control-M is a WLA software developed by BMC Software to automate and manage complex workflows.

Pros:

• Integration: Control-M received high score for application integration with 9.5 out of 48 reviews on Trustradius. ⁵

Cons:

• Ease of use and set-up: Control-M obtains 8.8 and 8.4 for ease of use and ease of set-up on G2 because some users find the tool too complicated to adopt at first since it requires dedicated administration and training. ⁶

Discover more on Control-M and its alternatives.

4. DBT

Dbt (Data Build Tool) is an open source tool to transform, test, and document data in a reproducible and maintainable way. It integrates with SQL-based databases to: 

• Write modular SQL transformations
• Manage dependencies between them
• Documenting the data pipeline.

Dbt is mainly a data transformation and modeling tool with DWA functionalities. 

Pros:

• Modularity and Reusability: DBT promotes modular and reusable code, making it easier to maintain and update data transformation logic.
• Testing and Documentation: It provides features for unit testing, documentation generation, and data lineage, ensuring code quality and data governance.

Cons:

• Limited ETL Functionality: DBT primarily focuses on data transformations and may not cover all aspects of traditional ETL (Extract, Transform, Load) processes.
• Slow load time: Some users complain about slow load times on the cloud (See Figure 4). 

5. TimeXtender

TimeXtender is a data management platform that simplifies the process of building and managing data warehouses and data lakes.TimeXtender also provides features like: 

• Data integration and transformation
• Data lineage tracking
• Automated data modeling 
• Automated data warehouse creation and ETL processes

Pros:

• Code generation and reusability: Generates optimized SQL code and promotes code reusability, making it easier to maintain and update data warehouse structures.
• Self-Service BI: Provides self-service capabilities for business users to explore and analyze data through a user-friendly interface.

Cons:

• Learning Curve: The tool may require training and expertise to fully utilize its capabilities and optimize data warehouse automation.

6. ZAP datahub

ZAP DataHub is a data management and analytics platform that simplifies access to, integration of, and analysis of data from multiple sources. It includes features such as

• Centralized data hub with structured and unstructured data
• Data governance
• Data integration from various sources. 

Pros:

• Pre-Built connectors and data models: Provides pre-built connectors and data models for popular data sources and applications, enabling faster implementation.

Cons:

• Customization Limitations: ZAP Data Hub’s pre-built connectors and data models may not cover all unique or custom data sources and applications.

7. Wherescape Red

WhereScape Red is a data warehouse automation tool that simplifies and accelerates the development, deployment, and management of data warehouses and data integration processes. It automates the creation of data warehouse structures and ETL (Extract, Transform, Load) workflows by designing and creating the necessary code. 

Pros:

• Code generation and reusability: It generates optimized code for data integration and transformation tasks, promoting code reusability and ease of maintenance.

Cons:

• Learning curve: The tool may require training and expertise to fully utilize its capabilities and maximize data warehouse automation.

8. Oracle autonomous data warehouse

Oracle Autonomous Data Warehouse is a cloud-based data warehousing solution offered by Oracle. It leverages machine learning and automation to deliver a self-driving, self-securing, and self-repairing data warehouse. 

Pros:

• Fully Managed Service: Oracle ADW is a cloud-based, fully managed data warehouse service, eliminating the need for infrastructure management and maintenance.
• Performance and Scalability: Offers high-performance query processing and scalability to handle growing data workloads.
• Autonomous Capabilities: Incorporates autonomous features such as self-tuning, self-repairing, and self-securing, reducing administrative overhead.

Cons:

• Vendor Lock-in: As a cloud-based service, Oracle ADW ties users to the Oracle ecosystem and may limit flexibility to migrate to other platforms.
• Limited integrations: Some users recommend data connections to different applications. 

9. Astera DW Builder

Astera DW Builder is a powerful data warehouse design and development tool that simplifies the process of building data warehouses and ETL (Extract, Transform, Load) workflows.It supports advanced data transformations, data cleansing, and data validation processes.

Pros:

• Ease of use: Astera offers a visual interface and intuitive drag-and-drop functionality, allowing users to easily design and model data warehouse structures. 
• Integration: With built-in connectors and data integration capabilities, DW Builder facilitates seamless extraction, transformation, and loading of data from various sources into the data warehouse. 

 Cons:

•  Re-usability: Users experience difficulty to use existing data flows again. 

10. Datavault Builder

DataVault Builder is a data modeling and automation tool designed to facilitate the implementation of Data Vault 2.0 methodology which helps organizations build scalable, flexible, and agile data warehouses. 

Datavault Builder can design Data Vault models and generate ETL (Extract, Transform, Load) code. The tool supports the creation of hubs, links, and satellites, and automates the generation of staging tables and ETL processes.

Pros:

• Easy to use and set-up: Users voted favorable for the easy interface the tool has and flawless set-up phase. 
• Flexibility: Datavault Builder has a flexible architecture and a large number of native connectors for different source systems and object storage.

Cons:

• Learning curve: Some users claim that Data Vault methodology requires expertise for effective use of the tool. 

Key capabilities for market leaders

Once you identify your shortlist of vendors among the market leaders outlined above, you can analyze them in detail across the dimensions below. Every company’s analysis in these domains will be a bit different since these categories include company specific or subjective criteria. For example:

• Your company’s preferred integrations will depend on your company’s current or planned tech stack
• Low code automation capabilities help software usability and evaluation of usability is a partially subjective. Users would need to evaluate the software in terms of usability.

Integrations

High volume data warehouses need to pull data from many downstream sources including relational databases, multiple operational systems (e.g. CRM, ERP). This data will need to feed upstream systems like business intelligence systems. It is important to ensure that your chosen DWA tool can achieve easy data integration with your tech stack.

Low code automation capabilities

Data warehouse automation is about reducing manual coding, therefore it is critical for data warehouse automation software to offer an easy-to-use low-code user interface.

ETL testing automation 

Data warehouse automation activities include data integration, transformation, workflow orchestration, schema management, and ETL testing. ETL (extract, transform, load) testing automation emerges as a specific type of data warehouse automation. It validates and verifies data movement and transformation in the ETL processes. ETL testing automation ensures accuracy, completeness and consistency by 

• Checking data extraction and transformation follow business rules 
• Comparing source data with transformed data. 

Typically, data warehouse automation solutions provide ETL-testing automation. However, there are also some tools that exclusively focus on ETL testing automation. Some of these tools are:

• Bitwise QualiDI
• Informatica Data Validation 
• Datagaps ETL Validator

In our shortlist, we did not include these ETL testing-specific solutions and rather chose comprehensive automation tools that can offer ETL testing automation under their platform. 

How to choose the right data warehouse automation software for your business?

Identifying the right data warehouse automation solutions is related to your business’ requirements, goals and infrastructure. For example, if you rely mostly on a specific tech giant’s tech stack (e.g. Oracle) in your business, then adopting a data warehouse automation tool that the giant provides could: 

• Streamline your adoption process 
• Reduce vendor sprawl

On the other hand, if you need a broad IT automation suite, workload automation solutions like ActiveBatch and RunMyJobs can better correspond to your needs.

If you require further assistance in your product selection process:

Transparency Statement

Numerous emerging tech firms, such as Redwood, are sponsors of AIMultiple.

External links

• 1.  “ActiveBatch Reviews.” G2. Revisited January 9, 2023.
• 2. “Redwood Reviews.” G2. Revisited January 9, 2023.
• 3. “Redwood RunMyJob user review” Peerspot. Revisited May 30, 2023.
• 4. “Redwood Reviews.” PeerSpot. Revisited January 9, 2023.
• 5.  “Control-M feature reviews.” Trustradius. Revisited June 7, 2023.
• 6.  “Control-M reviews.” G2. Revisited June 7, 2023.
• 7. “DBT user reviews” Trustradius. Revisited May 29, 2023.
• 8. “Wherescape Red User Reviews.” G2. Revisited May 30, 2023.
• 9. “Oracle autonomous data warehouse user review” G2. Revisited May 29, 2023.