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Make.com VS Apache Spark

Compare Make.com VS Apache Spark and see what are their differences

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Make.com logo Make.com

Tool for workflow automation (Former Integromat)

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
  • Make.com Landing page
    Landing page //
    2022-07-05
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Make.com features and specs

  • Ease of Use
    Make.com offers a user-friendly interface with drag-and-drop functionality, making it accessible for non-technical users.
  • Integration Options
    The platform supports a wide array of integrations with popular apps and services, enabling complex workflows.
  • Custom Workflows
    Users can create highly customized workflows tailored to specific business needs, allowing for greater flexibility.
  • Scalability
    Make.com is built to handle both small-scale and enterprise-level tasks, providing a scalable solution as your business grows.
  • Community and Support
    There is an active community and comprehensive support, including documentation and forums, to help users troubleshoot and optimize their usage.
  • Real-time Monitoring and Analytics
    The platform offers real-time monitoring and analytics, allowing users to track the performance of their workflows and make data-driven decisions.
  • Versatile Triggers and Actions
    Make.com offers a variety of triggers and actions that can be used to automate a wide range of tasks across different services.

Possible disadvantages of Make.com

  • Pricing
    The pricing structure can be expensive for small businesses or individual users, especially for advanced features and high-volume usage.
  • Learning Curve
    Despite its user-friendly design, there is still a learning curve for newcomers to understand all the capabilities and features.
  • Occasional Bugs
    Users have reported occasional bugs and issues, which can disrupt workflows and require troubleshooting.
  • Limited Offline Support
    Make.com heavily relies on internet connectivity, which can be a drawback for users requiring offline functionality.
  • Complexity for Advanced Features
    While basic workflows are easy to set up, leveraging more advanced features may require a deeper understanding of the platform and potentially some coding knowledge.
  • Dependency on Third-party Services
    The platform’s effectiveness is influenced by the reliability and performance of third-party services it integrates with, making it susceptible to external issues.
  • Data Privacy Concerns
    Storing and processing data through third-party services may raise privacy and compliance issues for businesses dealing with sensitive information.

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

Analysis of Make.com

Overall verdict

  • Overall, Make.com is considered a good platform for those looking to streamline processes and improve efficiency through automation. Its flexible and powerful features cater to a wide range of needs, although there may be a learning curve for those new to automation or with limited technical knowledge.

Why this product is good

  • Make.com, formerly known as Integromat, is a popular platform for automating workflows and integrating various software tools. It offers a visual interface that allows users to connect different applications and automate repetitive tasks, enhancing productivity. Its ability to create complex multi-step automations with various conditions and triggers makes it a robust tool for both small businesses and larger enterprises.

Recommended for

  • small business owners
  • project managers
  • IT professionals
  • digital marketers
  • anyone looking to automate tasks without extensive coding knowledge

Analysis of Apache Spark

Overall verdict

  • Yes, Apache Spark is generally considered good, especially for organizations and individuals that require efficient and fast data processing capabilities. It is well-supported, frequently updated, and widely adopted in the industry, making it a reliable choice for big data solutions.

Why this product is good

  • Apache Spark is highly valued because it provides a fast and general-purpose cluster-computing framework for big data processing. It offers extensive libraries for SQL, streaming, machine learning, and graph processing, making it versatile for various data processing needs. Its in-memory computing capability boosts the processing speed significantly compared to traditional disk-based processing. Additionally, Spark integrates well with Hadoop and other big data tools, providing a seamless ecosystem for large-scale data analysis.

Recommended for

  • Data scientists and engineers working with large datasets.
  • Organizations leveraging machine learning and analytics for decision-making.
  • Businesses needing real-time data processing capabilities.
  • Developers looking to integrate with Hadoop ecosystems.
  • Teams requiring robust support for multiple data sources and formats.

Make.com videos

+ Add

Zapier vs Integromat - Quick Comparison Review

More videos:

  • Review - Integromat feature tour
  • Review - Introduction to Integromat

Apache Spark videos

+ Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Category Popularity

0-100% (relative to Make.com and Apache Spark)

Make.com

Apache Spark

Automation
100 100%
Automation
0% 0
Databases
0 0%
Databases
100% 100
Web Service Automation
100 100%
Web Service Automation
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Make.com and Apache Spark

Make.com Reviews

The Best n8n.io Alternatives for Workflow Automation in 2025
Make, formerly known as Integromat, is a versatile no-code platform that enables users to create sophisticated workflows with ease. It offers a visual workflow builder that allows users to connect various applications and services, define conditional logic, and manipulate data without writing any code. Make's strengths lie in its ability to handle complex workflows and its...
Source: latenode.com
N8n.io Alternatives
One of the standout features of Integromat is its flexibility and customization options. Users can set up multi-step workflows with conditional logic, ensuring that each automation is tailored to their specific needs. Additionally, Integromat offers advanced error handling and data manipulation capabilities, providing robust solutions for complex automation requirements. For...
Source: apix-drive.com
The Best MuleSoft Alternatives [2024]
Make (formerly Integromat) is an integration solution that allows you to automate and connect applications, databases, web services, chatbots, and other systems.
Source: exalate.com
Top 9 MuleSoft Alternatives & Competitors in 2024
Make, one of the best Mulesoft alternatives, the ultimate IT process automation tool for enhancing efficiency, productivity, and collaboration. By automating routine tasks, integrating with existing infrastructure, and offering powerful workflow automation, Make empowers your team to streamline processes and achieve remarkable results.
Source: www.zluri.com
Zapier vs. Make.com: Which Automation Tool Will Take the Business Lead?
Make.com offers a cost-effective option for those looking for a business process automation solution, even if it may compromise usability and integration. From your scenario, Make.com seems like a realistic alternative for those with a more limited budget or those willing to work with additional API documentation and webhooks instead of the broader integration that Zapier...
Source: www.listproductsreview.com

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Apache Spark seems to be more popular. It has been mentiond 70 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Make.com mentions (0)

We have not tracked any mentions of Make.com yet. Tracking of Make.com recommendations started around Mar 2021.

Apache Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / about 1 month ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / about 1 month ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 3 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 3 months ago
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What are some alternatives?

When comparing Make.com and Apache Spark, you can also consider the following products

Zapier - Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

Hadoop - Open-source software for reliable, scalable, distributed computing

n8n.io - Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

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