Make and Zapier are two of the most popular automation platforms. With their help, you can connect various apps and services and create powerful workflows.

In this article, we'll provide an in-depth comparison of Make vs Zapier, focusing on key aspects such as pricing, integrations, user management, API capabilities, error handling, scalability, AI automation, and others.

And there is more – we'll take a close look at n8n, a source-available workflow automation tool. We’ll see what makes it a powerful alternative to both Make and Zapier, and compare its features with those of the two platforms.


Although Make and Zapier offer similar functionality, there are distinct differences that may make one better suited to your needs than the other. Zapier is a good starting point for non-tech users who are exploring automation, while Make is more robust for building advanced scenarios.

In the second half of the article, we will suggest n8n – an alternative tool that offers exceptional flexibility and scalability. So stay tuned or jump right to the Make vs Zapier vs n8n section.
Make vs Zapier vs n8n
Make vs Zapier vs n8n
  • Pricing: both Make and Zapier charge per individual operation, whereas n8n charges only per workflow execution.
  • Pre-built connectors: Make has 1500+, Zapier has 6000+, n8n offers 1000+ (some of them require additional credentials set up). All three platforms allow you to make custom requests, but n8n has easier ways to do this.
  • Compared to Zapier, Make has more robust error handling, collaboration, and user management features, especially on higher-tier plans. n8n supports basic team management on paid tiers and extended functionality on the Enterprise plan.
  • Make is better suited for complex workflows and high data volumes; Zapier is easier to expand but has limitations in customization and handling complex workflows. n8n has unique nodes for data transformations and allows the creation of highly flexible workflows with multiple triggers.
  • Coding: both Make and Zapier impose significantly limited custom scripting, while n8n could be much more attractive to developers.

Make vs Zapier – Which is the best?

Feature Make Zapier
Pricing model Charge for each
individual operation
Charge for each
individual task
Number of pre-built
1500+ 6000+
Custom connectors Yes, create custom apps and
make custom HTTP requests
Yes, via the Zapier Developer
Platform or custom outgoing webhooks
Coding features Built-in functions or limited custom
JS functions on Enterprise plan
Code by Zapier supporting
JS and Python, with limitations
Error handling Robust error handling options
like ignore, resume, rollback, etc.
Basic error
handling steps
Collaboration Sharing and
exporting scenarios
Sharing only on
Team plan and above
User management Advanced roles and permissions
on Teams and Org levels
Multiple users only on
Team plan and above
Data storage Data Stores feature
similar to databases
Tables feature to
store and manage data
Customization and
Designed to handle
complex workflows
Easy to expand, but limited
customization and complex workflows
Ease-of-use and
User-friendly interface,
suitable for non-technical users
Easiest to get started, ideal for
beginners and non-technical users

Make vs Zapier: A closer look

After comparing Make and Zapier at a high level, let's explore some of the key aspects that differentiate these two platforms.


Key takeaway: Make is generally more affordable for complex workflows, while Zapier's pricing can increase quickly as your automations grow.

A rule of thumb for calculating usage for both Zapier and Make is simple: multiply the number of data elements by the number of steps performed in the automation. charges by operation. Each time a module in a scenario performs an action, it counts as one operation. The first module always counts as one operation, even if it doesn’t return a bundle (a data element). Router modules and error handlers do not count as operations.

Make pricing in May 2024
Make pricing in May 2024

Zapier charges by task in a similar fashion. A task is a single data element that has been successfully processed in a single action step.

For example, a Zap receives an email with a single attachment, uploads an attachment to Dropbox and sends a Slack message. In this case, the data flows through one Trigger, two action steps and consumes 2 tasks. If 10 emails arrive at once, the Zap will consume 20 tasks (10 tasks for each action step).

Certain things do not count as tasks, such as all Triggers (first step of each Zap), Filters, Paths and various internal actions like Formatter, Delay, Looping and some others.

Zapier pricing as of May 2024
Zapier pricing as of May 2024

Finally, both and Zapier offer a modest free tier, but with significant feature gating even for basic functions. Make’s pricing is more affordable, whereas Zapier's costs skyrocket very quickly. Both platforms allow you to purchase ad-hoc steps and operations if you exceed their monthly quotas.


Key takeaway: Make and Zapier offer a wide range of integrations, with Zapier having a larger library of pre-built apps. Both Make and Zapier allow for custom requests.

It’s important to note that a ready-made integration may not cover all features. Therefore, the larger number of connectors does not immediately mean a better workflow development experience. We recommend that you take a closer look at integrations that are important to you in advance. This will give you accurate information and allow you to correctly estimate the workload.

Make offers a library of over 1500 pre-built connectors for popular apps and services, as well as the ability to create custom connectors via various HTTP Modules. This allows users to integrate a variety of tools and platforms, even if they are not included in the Make library. There are seven HTTP Modules for different use-cases, so things can get pretty confusing rather fast.

Generic Make Module for HTTP Requests
Generic Make Module for HTTP Requests. There are six more for downloading files, making authenticated requests etc.

Zapier, on the other hand, has an impressive library of more than 6000 pre-built apps, covering most of the common tools and services used by businesses. However, if a specific app is not available, users can send a custom request. This is done via a premium Webhook Action, meaning that it's completely not available for the free-tier users.

Zapier’s outgoing Webhook action
Zapier’s Webhook action is a bit limited compared to Make’s HTTP Modules and is available only for paid users

Both platforms have advanced developer portals for creating custom integrations via their Web UI.

User management

Key takeaway: Make and Zapier offer multi-user accounts, but Make supports a more advanced account management system with programmatic access via API.

Make supports organization accounts with unlimited users right from the start. The advanced Team features are available from the Team plan onwards. With a two-level role system (organization and team roles), there is enough granularity and control over the entire account. This allows organizations to assign specific permissions to each user based on their responsibilities and the level of access required. Finally, Make’s API supports programmatic control over the entire organization, including user management.

Zapier allows multiple users in a single account only on the Team and Enterprise plans:

  • There are several basic roles for the Team account;
  • Account users can share Zaps, folders and credentials;
  • The Enterprise plan offers even more granularity, but at the time of writing, we could not test these features.

Coding features

Key takeaway: Zapier offers fairly limited coding capabilities in JS and Python. Make only supports custom JS scripting on the Enterprise plan, so all other users will have to rely on workarounds.

Make provides the following:

  1. Built-in functions for simple manipulations with strings, arrays and dates.
  • Several logical operators are also supported.
  • These functions work as snippets and have a non-standard syntax.
  • However, looking at the functions' purpose, we can see that most of them have JavaScript equivalents and should be familiar to advanced users.

2. Custom JS functions are only available for Enterprise plan users and are subject to strict limitations: only ES6 version of JavaScript, no custom libraries, 300 ms execution time cap, max 5000 characters, no HTTP requests.

If you want to extend your scenarios with custom code, you should use third-party services such as AWS Lambda, Google Cloud Functions and some others.

Zapier, on the other hand, supports custom scripting via the Code by Zapier action:

  • Two languages are available: JavaScript (Node.js 14 modules + fetch) and vanilla Python (ver. 3.7.2).
  • When working with the JS, users can perform data filtering, variable creation, advanced table lookups and data requests.
  • StoreClient is a unique feature that supports the storage of small amounts of data between Zap runs.
  • Zapier’s coding functionality has rather strict limits on input data. Scripts are run on AWS Lambda with an 6Mb I/O cap.

AI features

Key takeaway: Make and Zapier offer a variety of integrations with popular AI-services. AI-powered tools to improve workflow automation are also available on both platforms.

Make offers a wide range of AI integrations, including OpenAI (ChatGPT, Whisper, DALL-E), Google Cloud Vision, Eleven Labs, Eden AI and Cloudinary. These integrations allow users to perform tasks such as summarizing emails, personalizing messages, converting text to audio and much more.

Additionally, Make's AI Assistant helps users build scenarios by understanding natural language prompts and suggesting relevant modules.

Zapier has recently expanded the use of AI on its platform. Beyond connecting third-party AI services, Zapier offers several native features:

  • Zap Guesser suggests automations based on user input;
  • Copilot, an AI assistant that helps users build Zaps faster;
  • The platform also offers AI-powered chatbots (in beta) to serve customers and employees, as well as AI fields in Zapier Tables for sentiment analysis and content summarization;
  • Finally, Zapier Central (in preview) allows users to work with AI-powered bots that understand their business, while Canvas (in beta) enables users to visually map out processes and receive AI-recommended improvements.
While Make and Zapier connect with many AI tools, neither of these platforms are particularly suited for creating LLM-powered services. In n8n we have implemented many of the LangChain nodes for an easy creation of complete LLM-apps, be it another chatbot with RAG functionality, an AI agent capable of searching the internet or a bot that summarizes video calls and long audio messages.

Data storage and management

Key takeaway: Both Make and Zapier offer built-in data storage options, but they differ in their approach and flexibility.

Make offers a feature called "Data stores" that allows users to store and manage data within the platform. The data stores in Make are similar to simple databases and allow users to add, replace, update, retrieve, delete, search and count records. Users can create multiple data stores, each with its own data structure, and allocate storage space from their total internal data storage capacity, which varies based on their plan.

After setting up a data structure, users can manipulate data stores manually via UI or from scenarios
After setting up a data structure, users can manipulate data stores manually via UI or from scenarios

Zapier also offers data storage via Zapier Tables, which allows users to store and manage data directly on the platform. Zapier Tables provides a user-friendly interface for creating tables, adding records and integrating with other apps and workflows.

Zapier’s Tables are a bit easier to set up and allow connecting to Zaps directly from the UI
Zapier’s Tables are a bit easier to set up and allow connecting to Zaps directly from the UI

While both platforms offer built-in data storage, Make's data stores offer more flexibility and control over data structure and storage allocation. However, users need to be aware of the challenges that come with updating the data structure in Make and should always create backups before making significant changes.

Error handling and monitoring

Key takeaway: Both platforms offer error handling and monitoring capabilities, but Make offers advanced options for customizing error handling scenarios, saving incomplete executions, and managing email notifications.

Make offers robust error handling features, such as setting up error handlers to deal with errors or unexpected events in your scenario. Users can choose from five error handlers:

  • Ignore
  • Resume
  • Commit
  • Rollback
  • Break.

Make also allows incomplete executions to be saved when an error occurs so that users can investigate and resolve issues. Additionally, Make provides customizable email notifications for warnings, errors and scenario deactivations due to errors.

Advanced error handling example in
Advanced error handling example in Source:

Zapier provides options for error handling, including the ability to add error handling steps to each step in a Zap (except for the Trigger and Paths steps). These error handling steps allow users to customize how their Zaps run when an error occurs. Zapier also offers manual and automatic replay options for failed Zap runs. However, Zapier's error handling capabilities may not be as extensive as Make's, especially when it comes to customizing error handling scenarios and storing incomplete executions.

An example of error handling in Zapier
An example of error handling in Zapier
In n8n users can create dedicated error workflows and easily connect them to the main workflows. This is a simple way to avoid repetitions. Of course, complex error handling of the individual nodes is also supported.

Collaboration and sharing

Key takeaway: Make enables sharing and exporting workflows, facilitating collaboration and reusability, while Zapier's sharing options are limited to the Team plan.

Make allows users to share and export their workflows, making it easier for team members to collaborate and reuse successful automation templates. This can be particularly useful for organizations with multiple departments or teams working on similar processes.

Sharing Zaps through Zapier is only available from the Team plan onwards, which may limit collaboration opportunities for users on lower-tier plans. Similarly, Zap export / import only works on the Teams and Enterprise plans.

Customization and flexibility

Key takeaway: Both platforms offer customization options. While Make offers a more flexible and extensible environment for complex workflows, Zapier stands out with several complementary features that extend basic automations.

Make is designed to handle complex workflows and allows moving larger volumes of data at the same budget, offering a scalable and extensible platform. Users can create custom modules, use built-in functions, and leverage the API for further customization. The enterprise plan includes an on-prem module for clients and a mobile app for automating actions on the end-user device.

Zapier also offers customization options, such as Code by Zapier and the ability to create custom integrations. However, Zapier can face challenges when dealing with highly complex workflows or large amounts of data, as there are some limitations on execution time and memory usage for custom code. On the other hand, Zapier offers services such as Interfaces, Chatbots and Canvas. With these tools, users can extend the basic functionality and create apps or collaborate on automating business processes.

In summary, both Make and Zapier are established products with a large user base. Although they may seem similar at first glance, there are significant differences in pricing, integrations, user management, coding features and other aspects. Which platform is best suited to your company depends on your specific needs and priorities.

Make and Zapier alternative: n8n

While Make and Zapier are both powerful automation platforms, there is another alternative worth considering: n8n – a source-available workflow automation tool.

Overview: Make vs Zapier vs n8n

Make vs Zapier vs n8n – Key terms
Make vs Zapier vs n8n – Key terms

Zapier and Make have given millions of ordinary users superpowers, enabling them to automate tasks – something that was previously only possible for developers. With the huge community, abundance of training material and ease of access, these platforms are true leaders in their fields.

n8n was originally developed as a tool to help developers avoid repetitive and tedious tasks such as setting up environments and servers, configuring credentials and sifting through API docs. Soon after its launch, many people appreciated the node-based interface and the ability to easily connect services without any coding (although coding was always a strong point of n8n).

In 2024, n8n already achieved feature parity with Make and Zapier when it comes to automation, offering several unique characteristics not found in these two platforms. The main difference of n8n lies in these areas:

  • Licensing and pricing;
  • Enterprise readiness;
  • Coding and developer tools;
  • Scalability and extensibility;
  • AI-capabilities for making complete services (chatbots, agents, RAG, vector store, custom tools and more).

Licensing and pricing

n8n comes with a fair-code source-available license. This means that anyone with the appropriate knowledge can self-host it or even inspect the product codebase.

In terms of pricing, n8n offers several cost-effective options. Although there’s no free tier for the cloud offering (apart from a trial period), only workflow executions are charged.

Regardless of the workflow complexity and the amount of data – a single run counts only +1 towards the quota.

For some automations, n8n can be 1000 times more cost-efficient compared to Zapier or Make. Only a fraction of users who have very modest requirements would find n8n more expensive compared to alternative platforms.

On top of that, there is no feature gate on core functionality: no premium nodes, all users are equally able to build complex workflows regardless of their pricing plan. At the higher tiers, users have more options for team collaboration or advanced enterprise features, but the workflow-building experience is the same for all users.

Make vs Zapier vs n8n: pricing model
Make vs Zapier vs n8n: pricing model

Enterprise readiness

Although n8n offers a completely free option for self-hosting, its true value lies in an Enterprise offering.

Organizations have everything they need to roll-out an on-prem version of n8n, including: advanced security features and audit logs.

  • External secrets vault: n8n's integration with external secrets stores (like HashiCorp Vault) centralizes sensitive data management, enhances security, and streamlines compliance.
  • RBAC (Role-Based Access Control) in n8n enhances efficiency and security by enabling granular access management within team environments.
  • Environments & version control - n8n utilizes GitHub for rigorous version control across production and non-production environments, minimizing deployment risks and promoting stable, continuous innovation.
  • n8n's Queue Mode enhances scalability by distributing workflow executions across multiple worker instances, dynamically adjusting capacity to meet demand and optimize resource use.

This is an especially sought-after set of features that are not available in Zapier or Make. This makes n8n an ideal product for supporting even the most business-critical operations in regulated industries.

Startups are also eligible for a dedicated plan.

Coding and building products

The no-code side of n8n is complemented by a strong ability to write code and even build complete products. Let’s see what developers might find particularly appealing about n8n.

n8n users have an overview of a node’s input / output data on a single screen
n8n users have an overview of a node’s input / output data on a single screen

First, n8n supports expressions. These seemingly short JS snippets can save a lot of time and help design effective workflows thanks to the built-in support of Luxon and JMESPath libraries. Both data transformations and node settings support expressions. This makes workflows robust and compact, avoiding unnecessary IF switches.

Second, is the Code node. Here you can write custom logic and advanced functionality in JavaScript or Python. Users that run n8n in self-hosted mode can even install 3rd-party npm libraries, access filesystem and make HTTP requests.

Take a look at the screenshot of a real project. In this example, the Code node has access to an external npm library (nunjucks) and writes a file directly to the filesystem.

The Code node has access to external libraries and a filesystem
The Code node has access to external libraries and a filesystem

Scalability and extensibility

We’ve already covered the possibility of extending n8n with npm packages. But that’s just scratching the surface:

  • You can give n8n access to custom system tools or fully integrate it into your systems.
  • n8n can run as a single instance or in a robust queue mode.
  • Ultimately, you can roll out n8n on a Kubernetes cluster.

When it comes to extending nodes, n8n enables the creation of community integrations for third-party services or nodes that improve workflow building experience.

Creating AI-powered products

Last but not least, if you want to create an AI-powered project, n8n offers you a good solution with LangChain support. Almost 70 dedicated nodes allow you to build a complete back-end for:

  • LLM-chatbots;
  • OpenAI assistants;
  • Retrieval-Augmented Generation (RAG) workflows with in-memory storage or vector databases (Supabase, Qdrant, Pinecone and Zep);
  • AI-powered agents (conversational, function calling, plan and execute, ReAct);
  • Custom tools (including n8n-workflows as tools);
  • Simple workflows with document loading, text splitting and embeddings.

While building these products, you can use popular LLMs from OpenAI, Antropic, Mistral and HuggingFace, or custom model endpoints including completely self-hosted LLMs.

As usual, there’s a special node for custom code that supports the langchain.js library.

An example of a LangChain agent which runs n8n workflow as a tool
An example of a LangChain agent which runs n8n workflow as a tool

Comparison table of Make, Zapier, and n8n

To help you compare n8n with Make and Zapier, here's a table highlighting some of the key features and differences:

Feature n8n Make Zapier
Pricing model Charge per workflow,
no limit on tasks / steps
Charge for each
individual operation
Charge for each task
Self-hosting Yes, free tier
and Enterprise
No No
Yes, via HTTP node (easy)
OR write and deploy your
own n8n nodes (advanced)
Yes, create custom apps
via Web UI and make
custom HTTP requests
Yes, via the Dev Platform or
custom outgoing webhooks
with some limits
Coding features Built-in JS/Python support,
install external packages
when self-hosting
Limited custom JS
functions only on
Enterprise plan
Code by Zapier
supporting JS and Python,
with limitations
Error handling Customizable error
handling workflows
Robust error handling
options like ignore,
resume, rollback, etc.
Limited error
handling steps
Collaboration Sharing and exporting
workflows and credentials
from Starter tier
Sharing and
exporting scenarios
Sharing only on
Team plan and above
Unlimited number of users
on all plans, basic user
management from Pro tier
Advanced roles and
permissions on Teams
and Org levels
Multiple users only on
Team plan and above
AI features AI-driven workflows via
LangChain and Ask AI
to generate code
Common AI integrations
and an AI-powered tool
for making scenarios
AI-powered Zap builder,
Formatter with AI,
Code with AI
Data storage Only small amount
of data is stored as
part of the workflow
Data Stores feature,
similar to databases
Zapier Tables feature
to store and manage data
API Available on all plans,
mostly workflow and
execution functionality.
Limited user management
via API
API with advanced
features including
credentials and user
Observability API only
on Enterprise plan
Dedicated enterprise plan
with enhanced security
and unlimited workflows
Enterprise plan with
custom pricing
Enterprise plan with
an annual task limit
Scalability and
Highly scalable and
extensible, requires
additional configuration
Designed to handle
complex workflows and
high volumes of data
Easy to expand, but limited
customization and
complex workflows
Community and
Active community forum
that includes feature
requests voting and
bug-reports. This ensures
swift updates and fixes.
Community support,
company support on
paid tiers. Extensive
including the Academy
Community support,
premier support for
higher plans,
learning platform
Branching, looping,
merging data, dataset
comparison and error
handling within workflows
Complex workflows with
tools like Router module
and error handling
Multi-step Zaps and paths
for conditional logic,
but limited compared
to n8n and Make
Powerful JS expressions,
nodes for seamless data
conversion and a custom
code for advanced cases
Wide range of built-in
functions for data
Formatter and Code steps
for data manipulation,
with limitations

Wrap Up

In this article, we’ve thoroughly compared Make and Zapier – powerful automation platforms with their own strengths and weaknesses.

n8n emerges as a compelling alternative, especially for users who value cost-effectiveness, robust workflow building experience and developer-friendly features.

The choice of the platform depends on various factors, including the complexity of your automations, the integrations you require, the initial skills of your team and your budget.


Is Zapier the same as Make?

While Zapier and Make (formerly Integromat) are both automation platforms that connect different apps and services, they have some important differences.

Zapier focuses on simplicity and ease of use, offering a wide range of pre-built integrations and templates. In addition, Zapier has introduced several new features to its platform, such as Tables, Interfaces and Chatbots.

Make, on the other hand, offers more advanced features and flexibility, allowing users to create complex workflows and custom scenarios.

What are the limitations of Zapier?

One of Zapier's main limitations is its pricing structure. As your automations grow, the cost of using Zapier will increase significantly.

Zapier also has some limitations on the number of tasks and volume of data you can process, depending on your plan. Some users may also find Zapier's interface and workflow editor less flexible compared to other automation platforms like Make or n8n.

Can I trust Zapier?

Zapier is a well-established and respected automation platform that has been on the market since 2011. It has demonstrated its commitment to data privacy and compliance with applicable laws and participates in the EU-US Data Privacy Framework program.

It's important to understand that when using Zapier, you are considered the "data controller" and are responsible for complying with data protection laws. Zapier is responsible as a "data processor" for protecting the data that flows through its systems.

Is Zapier free of charge?

Zapier offers a modest free plan that allows you to create simple 2-step Zaps with limited features and task runs. This plan is only sufficient for occasional use or testing.

In most other cases, your automations will require an upgrade to a paid plan. Lower-tier paid plans are quite affordable. However, as your operations grow, you may see a steep price increase, which can be very burdensome, especially for small businesses or individuals.

Is Zapier worth the cost?

Whether Zapier is worth the cost depends on your specific needs and budget. In our experience, it’s easy to estimate the automation of transactions with a known ROI. One example is the processing of sales orders.

If you are automating routine tasks and especially trying to perform bulk data transfers, alternatives such as n8n may significantly outperform Zapier.

What’s next?

Now that you better understand the differences between Make and Zapier you can pick the right tool!

Or perhaps give n8n a try?

To learn more about the differences between n8n and its alternatives, check the in-depth articles on:
-> Make vs n8n
-> Zapier vs n8n

How to move to n8n from Make?

Migrating from Make to n8n is relatively straightforward, however there are currently no ready-made 1-click tools to translate Make scenarios into n8n workflows.

To start transferring scenarios, sign up for an n8n account, familiarize yourself with the workflow editor and view the documentation page. A quickstart guide and 2-level course will help you to get started.

n8n offers a wide range of nodes (integrations) covering most of the popular apps and services supported by Make. Custom integrations can be done via the HTTP node. If you have used functions in Make, then most of them have JavaScript expressions as equivalents.

Not all Make connectors are identical to the n8n nodes, so feel free to ask in a community forum for the best approaches.

How to move to n8n from Zapier?

Switching from Zapier to n8n is similar to switching from Make. Most likely, transferring Zaps will be easier due to its lower complexity.

However, you may encounter some hurdles if you make extensive use of other Zapier tools such as Tables, Interfaces or Chatbots.

Re-creating Zapier Chatbots is the easiest task among these three thanks to the powerful LangChain integration in n8n. There are currently no equivalents for Tables and Interfaces in n8n. This may seem like a downside at first glance, but it also means that you are not vendor-locked to a specific solution.

We can recommend trying out some of the no-code databases (such as NocoDB, Baserow, or SeaTable). They are all available in the cloud and via self-hosting and also offer certain features similar to Zapier interfaces. Airtable is another option, although it’s only available as a cloud SaaS.

Join the community forum and share your success or seek support! Remember, the key to successful automation is to start small, iterate often and always keep learning.