Automation Compare

Head-to-Head

Make vs Windmill

Our content is free to read, but we may earn an affiliate commission when you buy through our links. This helps fund our research.

Full category matrix: Developer & IT Automation

Data last reviewed:

Features
Make Visit Website ↗
Windmill Visit Website ↗
Priority
App Connectors Count
App Connectors Count Native implementation of a vast app ecosystem enables extensive integration possibilities, surpassing many competitors in scope. Crucially, the sheer volume of available integrations may introduce complexity in configuration and maintenance, demanding careful management.
10
Custom API & Webhooks
Custom API & Webhooks Circumvents standard API restrictions by enabling customizable request configurations, allowing for tailored integrations beyond preset parameters. However, the complexity of configuring these requests can introduce significant overhead, necessitating detailed knowledge of API structures.
10
Visual Workflow Builder
Visual Workflow Builder Within an intuitive interface, straightforward automations are constructed, though intricate workflows may need technical intervention.
9
Team Workspaces
Team Workspaces Team-based collaboration workspaces enable shared access and project management across multiple administrators. However, scaling these workspaces for larger teams may necessitate additional investment in higher-tier plans.
9
Visual Debugging
Visual Debugging Visual inspection tools in Make provide a graphical interface for debugging automation workflows, facilitating error identification. While effective for basic debugging, complex scenarios may require supplementary diagnostic methods to achieve thorough analysis.
9
Advanced Logic & Branching
Advanced Logic & Branching Native architecture ensures that offering a wide array of conditional and branching capabilities that enhance automation complexity. That said, implementing such complex logic may require significant computational resources, potentially impacting performance. Facilitates complex computational tasks through complex-logic capabilities that extend beyond basic automation functions. In practice, implementation demands specialized technical expertise, which may necessitate additional training or consulting resources.
9
Loops & Iterators
Loops & Iterators Iterative processing capabilities in Make allow for the execution of loops and iterators within workflows, facilitating repetitive task automation. However, extensive iteration may impact performance and credit consumption, necessitating careful design considerations. Loops-iterators facilitate repetitive task execution through efficient iteration processes, enhancing automation capabilities. That said, the complexity of iteration logic requires careful design to avoid inefficiencies or errors.
9
Custom Code Execution
Custom Code Execution Contrary to standard execution environments, custom code execution in Make is facilitated through a dynamic scripting interface that integrates natively with existing automation frameworks. However, the complexity of this feature necessitates careful monitoring of script performance to avoid excessive credit consumption. Bypasses typical execution constraints by offering direct API access for custom script deployment, ensuring high flexibility in automation. However, extensive usage may necessitate increased engineering resources to manage and optimize scripts effectively.
8
Error Handling & Retries
Error Handling & Retries Error-handling mechanisms in Make provide automated retries for failed operations, reducing manual intervention. While effective for basic scenarios, complex error conditions may require manual oversight and configuration adjustments. Granular logs and automated retries are embedded within the system to handle errors and maintain workflow continuity. In practice, more complex workflows may necessitate custom tuning of retry logic to meet specific operational demands.
8
Sub-workflows
Sub-workflows Nested workflow capabilities in Make allow for the creation of sub-workflows within larger automation processes, enhancing modularity. However, excessive nesting can complicate debugging and maintenance, requiring careful architectural planning.
8
Dedicated Support & SLA
Dedicated Support & SLA Different from standard support models, dedicated-support-SLA offers tailored assistance aligned with specific organizational needs. While this provides a high level of service, resource allocation for personalized support can be a limiting factor.
8
Enterprise Security & SSO
Enterprise Security & SSO Proprietary security protocols ensure data integrity and compliance through complex encryption and access control mechanisms. Crucially, scaling these protocols to match enterprise demands may necessitate custom configurations and increased resource allocation. Secures sensitive data through enterprise-security protocols that align with industry best practices. However, maintaining security integrity demands continuous monitoring and timely updates to counter emerging threats.
8
SOC2 & HIPAA Compliance
SOC2 & HIPAA Compliance Native compliance certifications ensure adherence to industry standards, providing a reliable framework for data security and privacy. While these certifications cover a wide range of requirements, specific industry needs may necessitate additional compliance measures. Ensures adherence to industry standards through compliance-certifications that align with current regulatory requirements. However, maintaining certification validity demands continuous updates in response to evolving regulations.
8
Parallel Processing
Parallel Processing Parallel execution frameworks in Make enable simultaneous task processing, significantly improving workflow efficiency. In practice, resource allocation constraints may limit the extent of parallelization achievable, impacting overall execution speed. Enables concurrent task execution through parallel-processing, significantly enhancing processing speed and efficiency. However, achieving efficient performance requires balanced resource distribution to prevent bottlenecks.
8
Batch Execution
Batch Execution Deployment of batch execution processes enables simultaneous processing of multiple operations, enhancing throughput beyond basic sequential execution. However, the complexity of managing concurrent operations may necessitate additional computational resources, potentially impacting system efficiency. Batch-execution capabilities enable the processing of large data sets concurrently, enhancing throughput efficiency. Crucially, resource allocation must be carefully managed to prevent performance bottlenecks during peak operations.
8
AI Agent Builder
AI Agent Builder Through the deployment of proprietary datasets, AI agents manage prompts with exceptional accuracy, surpassing standard capabilities.
7
Self-Hosted Deployment
Self-Hosted Deployment Native implementation of self-hosted deployments allows for enhanced data control and compliance with stringent regulations. However, resource management and alignment with compliance standards require careful planning and execution to avoid potential pitfalls.
7
Built-in Data Tables
Built-in Data Tables Different from external data storage solutions, built-in data tables facilitate direct access and manipulation of datasets within the platform, streamlining data-driven operations. In practice, the scalability of these tables may be constrained by data volume limitations, necessitating strategic data management.
7
AI Workflow Copilot
AI Workflow Copilot Granular logs generated by AI co-pilot functionalities provide detailed insights into automation processes, enhancing oversight. While these capabilities are beneficial, the integration of AI co-pilot features can be complex, requiring dedicated engineering resources to fully implement. Aggregates system data so that AI-copilot-generation utilizes machine learning to assist in code development and task execution. That said, maintaining model accuracy and relevance necessitates regular updates and tuning.
6
Real-Time Webhooks
Real-Time Webhooks Granular real-time triggers enable immediate response to data changes, enhancing operational responsiveness. While effective for straightforward workflows, complex scenarios may require additional resources to maintain efficient performance. Different from scheduled tasks, real-time-triggers activate processes immediately upon event detection, enabling responsive data management. While this enhances reactivity, latency issues in event-driven architectures can affect performance.
6
Web Scraping Actions
Web Scraping Actions Web data extraction capabilities in Make enable automated retrieval of online information, supporting diverse data collection needs. In practice, restrictions on scraping frequency and target site compatibility may limit the breadth of data accessible.
6
Data Transformation
Data Transformation Circumvents conventional transformation tools, allowing for intricate data manipulation directly within automated workflows through a reliable set of transformation functions. In practice, high-volume data processing may require additional computational resources, potentially impacting credit usage. Proprietary datasets are transformed natively through integrated functions that allow for real-time data manipulation and analysis. While the system facilitates wide-ranging transformations, the initial setup may require minor adjustments to align with specific data architecture requirements.
5
Active Community
Active Community In contrast to less engaged platforms, Make benefits from an active community that contributes to shared knowledge and problem-solving. In practice, community-driven support can be inconsistent, necessitating reliance on official documentation for complex issues. Community-driven documentation and forums provide a knowledge base that complements Windmill's code-first design. However, reliance on external resources can lead to inconsistencies in support quality.
5
Pre-built Templates
Pre-built Templates Bypasses manual setup requirements by offering a wide array of prebuilt templates for rapid deployment. However, customization beyond the provided templates may require additional configuration efforts.
5
Community Solutions
Community Solutions Proprietary community solutions offer a repository of shared knowledge and tools that enhance the platform's adaptability to diverse use cases. However, the variability in solution quality necessitates a cautious approach, often requiring validation against official documentation for complex implementations. Contrary to proprietary support channels, community-solutions utilize collective knowledge to provide diverse troubleshooting options. While the variability in solution quality can affect applicability, these resources offer valuable insights for problem-solving.
5
Version Control (Git)
Version Control (Git) By incorporating Git, basic tracking of workflow changes is achieved, yet extensive version control requires external tools. Version-control-git integrates natively with Windmill, supporting collaborative code management through branching and merging. That said, the complexity of these strategies requires careful planning to avoid conflicts and ensure code integrity.
4
Workflow Fit Index
Workflow Fit Index

Make

6.6 / 10

Windmill

4.8 / 10

Where Make and Windmill differ

Make documents 24 supported capabilities; Windmill documents 16. Unique coverage below links to each feature hub.

Only in Make

Only in Windmill

Choose between Make and Windmill

JP

Jakub Pajtinka

Lead Data Curator

Jakub analyzes integration connectors, evaluates execution limits, and aggregates real sentiment from RevOps communities to build objective workflow automation comparisons without the marketing fluff.

Connect on LinkedIn →

More Make and Windmill matchups