Software Alternatives, Accelerators & Startups

Apache Spark VS Camunda

Compare Apache Spark VS Camunda and see what are their differences

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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.

Camunda logo Camunda

The Universal Process Orchestrator
  • Apache Spark Landing page
    Landing page //
    2021-12-31
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

Camunda

$ Details
freemium
Release Date
2008 January
Startup details
Country
Germany
State
Berlin
City
Berlin
Founder(s)
Bernd Ruecker
Employees
250 - 499

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.

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.

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.

Analysis of Camunda

Overall verdict

  • Camunda is considered a good option for organizations looking to implement process automation and digital transformation projects. Its ability to handle complex workflows and compatibility with modern software practices makes it a strong candidate, especially for enterprises seeking robust and customizable solutions.

Why this product is good

  • Camunda is a powerful workflow and decision automation tool that is highly scalable and flexible. It offers an open-source platform with extensive capabilities for process automation and orchestration. It integrates well with microservices architectures and supports BPMN (Business Process Model and Notation) standards, making it accessible for both developers and business analysts. Additionally, it has strong community support and extensive documentation, which facilitates ease of use and troubleshooting.

Recommended for

  • Enterprises that require scalable process automation solutions
  • Organizations that prefer open-source tools
  • Teams using microservices architectures
  • Businesses looking for BPMN-standard support
  • Developers and business analysts collaborating on process improvement

Apache Spark videos

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

Camunda videos

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

More videos:

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

Category Popularity

0-100% (relative to Apache Spark and Camunda)
Databases
100 100%
0% 0
BPM
0 0%
100% 100
Big Data
100 100%
0% 0
Workflow Automation
0 0%
100% 100

Questions and Answers

As answered by people managing Apache Spark and Camunda.

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 Apache Spark and Camunda. 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 Apache Spark and Camunda

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...
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...
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...

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...
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.
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...
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

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Camunda. 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.

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 2 months 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 2 months 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 / 4 months ago
View more

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 / 4 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 / about 1 year 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
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What are some alternatives?

When comparing Apache Spark and Camunda, you can also consider the following products

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

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.

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

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.

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

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