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Camunda VS Scikit-learn

Compare Camunda VS Scikit-learn and see what are their differences

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Camunda logo Camunda

The Universal Process Orchestrator

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Not present

The leader in process orchestration, Camunda enables organizations to operationalize and automate AI, integrating human tasks, existing and future systems without compromising security, governance, or innovation. Built for business and IT to collaborate, Camunda empowers organizations to overcome complexity, increase efficiency, and retain their competitive advantage no matter what speed and scale are required. Over 700 top organizations across all industries, including Atlassian, ING, and Vodafone trust Camunda with the design, orchestration, automation, and improvement of their business-critical processes to accelerate digital transformation. To learn more visit camunda.com

  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Camunda

Website
camunda.com
Pricing URL
Official Camunda Pricing
$ Details
freemium
Release Date
2008 January
Startup details
Country
Germany
State
Berlin
City
Berlin
Founder(s)
Bernd Ruecker
Employees
250 - 499
Edit details

Scikit-learn

Website
scikit-learn.org
Pricing URL
-
$ Details
Release Date
-
Edit details

Camunda features and specs

  • Agentic Orchestration
    Build AI agents, automate documents with AI-powered IDP, and run RPA bots.
  • Process Orchestration
    Coordinate the various moving parts and endpoints of a business process and tie multiple processes together for true end-to-end automation.
  • Scalability
    Camunda is designed to handle large-scale process automation, making it suitable for enterprise usage.
  • Rich API's
    REST and Java APIs that allow for seamless integration with other software systems and applications.
  • Open architecture
    Customize any workflow to fit your needs.
  • Marketplace
    Your hub for Camunda Accelerators like out-of-box connectors, process blueprints, and the ability to contribute to and request new solutions.
  • Common visual language
    Supports the BPMN 2.0 standard for process modeling, enabling you to adapt faster as business and processes evolves.
  • SAP Integration
    Automate processes that span your Systems of Record.
  • Flexible Deployment
    Cloud and self-hosting licensing available, giving organizations the flexibility to choose their preferred environment.
  • Cockpit and Tasklist
    Includes powerful tools like Cockpit for monitoring and Tasklist for task management, enhancing the control over process execution.
  • Community Support
    A large and active user community provides support, plugins, and shared knowledge, which can be very useful for troubleshooting and extending the platform.
  • Documentation and Training
    Comprehensive documentation and training materials help teams get up to speed quickly with the platform.

Possible disadvantages of Camunda

  • Steep Learning Curve
    Due to its extensive features and capabilities, the platform can be complex for new users to learn and master.
  • Licensing Costs for Enterprise Features
    While the open-source version is free, the enterprise edition with advanced features can be costly.
  • Customization Complexity
    Highly customizable but may require significant development effort to tailor it to specific business needs.
  • Resource Intensive
    Can be resource-intensive, requiring robust hardware to run efficiently, particularly for large-scale deployments.
  • Limited Out-of-the-Box Integrations
    Fewer built-in integrations compared to some competitors, often necessitating custom development work.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Camunda videos

+ Add

CamundaCon 2018: The Role of Workflows in Microservices (Camunda)

More videos:

  • Review - 5 Camunda advanced topics
  • Review - Camunda, The Universal Process Orchestrator

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Camunda and Scikit-learn)

Camunda

Scikit-learn

BPM
100 100%
BPM
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Workflow Automation
100 100%
Workflow Automation
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

Questions and Answers

As answered by people managing Camunda and Scikit-learn.

Who are some of the biggest customers of your product?

Camunda's answer

likeMagic 24 Hour Fitness Atlassian Deutsche Telekom U.S. Department of Veterans Affairs Zalando Amdocs DB Cargo Helsana

User comments

Share your experience with using Camunda and Scikit-learn. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Camunda and Scikit-learn

Camunda Reviews

BPM Tools Comparison: Camunda for IT Pros vs Pneumatic for Business Users
Camunda doesn’t offer default deployments, you can’t just sign up for an account and start using it, you have to think first about how and where you plan to deploy your instance. It can be deployed on-premises or in the cloud and supports containerization technologies like Docker and Kubernetes, offering flexibility depending on the company’s IT strategy. Camunda also offers...
Source: www.pneumatic.app
7 Best Business Process Management Tools (2023)
Camunda provides one of the best developer communities to help your team design, build, and automate any complicated business process, with over 100.000 developers. Having such a large network is critical for your team to have a technical reference whenever needed.
Source: theecmconsultant.com
11 Business Process Management (BPM) Software for SMBs
With Camunda, you can connect, collaborate, and scale rapidly. Orchestrate Camunda into the process endpoints your organization needs to automate the flow and bring IT and business together to collaborate effectively.
Source: geekflare.com
12 of the Top-Rated Free and Open-Source BPM Software Solutions
Description: Camunda is an open-source software company providing process automation with a developer-friendly approach that is standards-based, highly scalable, and collaborative for business and IT. The vendor offers visibility into business operations and improves system resilience. The provider’s workflow and decision automation tools enable Camunda to build software...
Source: solutionsreview.com
Top 7 Workflow Software (2020 Reviews)
Camunda also offers Camunda Cloud — a workflow system that’s best for cloud computing workflows, like a shared service process.
Source: clickup.com

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Camunda. It has been mentiond 31 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.

Camunda mentions (17)

  • Automating Enhanced Due Diligence in Regulated Applications
    To put everything together, you need platforms like Drools and Camunda to store the complex rule sets and logic that determine the success or failure of a due diligence attempt. - Source: dev.to / 3 months ago
  • Workflow, from stateless to stateful
    In addition, I developed a Spring Boot application with Kotlin based on the Camunda platform. Camunda is a workflow engine. - Source: dev.to / 12 months ago
  • Optimizing Decision Making with a Trie Tree-Based Rules Engine: An Experience Report
    In Pictet Technologies, my team relies a lot on decision models. These models allow our business analysts to input Compliance business rules directly into the systems with minimal developer intervention. When I joined the company, we used to use both Drools and Camunda. However, we faced severe memory and performance issues, specifically with Camunda, prompting me to explore alternatives. - Source: dev.to / over 2 years ago
  • How to Communicate Your Process Visually using BPMN as Code
    BPMN is actually a set of standards has been used for years for complex enterprise processes, and nowadays it's becoming more accessible thanks to the development of the new techniques. Web based tooling (like Camunda, BPMN.io), more platforms supporting integrating diagrams into the flows, and remote work culture all helps us to use BPMN easier. Besides all of that, we drive/lead more and more initiatives... - Source: dev.to / over 2 years ago
  • How to Achieve Geo-redundancy with Zeebe
    Bernd Ruecker is co-founder and chief technologist of Camunda as well as the author ofPractical Process Automation with O’Reilly. He likes speaking about himself in the third person. He is passionate about developer-friendly process automation technology. Connect viaLinkedIn or follow him onTwitter. As always, he loves getting your feedback. Comment below orsend him an email. - Source: dev.to / almost 3 years ago
View more

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
View more

What are some alternatives?

When comparing Camunda and Scikit-learn, you can also consider the following products

Appian - See how Appian, leading provider of modern low-code and BPM software solutions, has helped transform the businesses of over 3.5 million users worldwide.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Bizagi - Bizagi is a Business Process Management (BPMS) solution for faster and flexible process automation. It's powerful yet intuitive BPM Suite is designed to make your business more agile.

OpenCV - OpenCV is the world's biggest computer vision library

Kintone - Build business apps and supercharge your company's productivity with kintone's all-in-one...

NumPy - NumPy is the fundamental package for scientific computing with Python

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