Software Alternatives & Reviews

Apache Camel VS Apache Spark

Compare Apache Camel VS Apache Spark and see what are their differences

Apache Camel logo Apache Camel

Apache Camel is a versatile open-source integration framework based on known enterprise integration patterns.

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.
  • Apache Camel Landing page
    Landing page //
    2021-12-14
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Apache Camel videos

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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

Category Popularity

0-100% (relative to Apache Camel and Apache Spark)
Data Integration
100 100%
0% 0
Databases
0 0%
100% 100
Web Service Automation
100 100%
0% 0
Big Data
0 0%
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 Apache Camel and Apache Spark

Apache Camel Reviews

10 Best Open Source ETL Tools for Data Integration
Popular for its data integration capabilities, Apache Camel supports most of the Enterprise Integration Patterns and newer integration patterns from microservice architectures. The idea is to help you solve your business integration problems using the best industry practices. It is also interesting to note that the tool runs standalone and is embeddable as a library within...
Source: testsigma.com
11 Best FREE Open-Source ETL Tools in 2024
Apache Camel is an Open-Source framework that helps you integrate different applications using multiple protocols and technologies. It helps configure routing and mediation rules by providing a Java-object-based implementation of Enterprise Integration Patterns (EIP), declarative Java-domain specific language, or by using an API.
Source: hevodata.com
Top 10 Popular Open-Source ETL Tools for 2021
Apache Camel is an Open-Source framework that helps you integrate different applications using multiple protocols and technologies. It helps configure routing and mediation rules by providing a Java-object-based implementation of Enterprise Integration Patterns (EIP), declarative Java-domain specific language, or by using an API.
Source: hevodata.com
Top ETL Tools For 2021...And The Case For Saying "No" To ETL
Apache Camel uses Uniform Resource Identifiers (URIs), a naming scheme used in Camel to refer to an endpoint that provides information such as which components are being used, the context path and the options applied against the component. There are more than 100 components used by Apache Camel, including FTP, JMX and HTTP. Apache Camel can be deployed as a standalone...
Source: blog.panoply.io

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...

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Apache Camel. It has been mentiond 56 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 Camel mentions (12)

  • Ask HN: What is the correct way to deal with pipelines?
    "correct" is a value judgement that depends on lots of different things. Only you can decide which tool is correct. Here are some ideas: - https://camel.apache.org/ - https://www.windmill.dev/ Your idea about a queue (in redis, or postgres, or sqlite, etc) is also totally valid. These off-the-shelf tools I listed probably wouldn't give you a huge advantage IMO. - Source: Hacker News / 7 months ago
  • Why messaging is much better than REST for inter-microservice communications
    This reminds me more of Apache Camel[0] than other things it's being compared to. > The process initiator puts a message on a queue, and another processor picks that up (probably on a different service, on a different host, and in different code base) - does some processing, and puts its (intermediate) result on another queue This is almost exactly the definition of message routing (ie: Camel). I'm a bit doubtful... - Source: Hacker News / about 1 year ago
  • Can I continuously write to a CSV file with a python script while a Java application is continuously reading from it?
    Since you're writing a Java app to consume this, I highly recommend Apache Camel to do the consuming of messages for it. You can trivially aim it at file systems, message queues, databases, web services and all manner of other sources to grab your data for you, and you can change your mind about what that source is, without having to rewrite most of your client code. Source: about 1 year ago
  • S3 to S3 transform
    For a simple sequential Pipeline, my goto would be Apache Camel. As soon as you want complexity its either Apache Nifi or a micro service architecture. Source: over 1 year ago
  • 🗞️ We have just released our JBang! catalog 🛍️
    🐪 Apache Camel : Camel JBang, A JBang-based Camel app for easily running Camel routes. - Source: dev.to / over 1 year ago
View more

Apache Spark mentions (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / about 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 4 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
View more

What are some alternatives?

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

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

StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

AFSAnalytics - AFSAnalytics.

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