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Celery VS Apache Spark

Compare Celery VS Apache Spark and see what are their differences

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  2. » Videos
  3. » Reviews
  4. » Alternatives

Celery logo Celery

Celery helps innovative companies set up pre-order or custom crowdfunding campaigns anywhere.

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.
  • Celery Landing page
    Landing page //
    2021-10-19
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Celery

Categories
  • Data Integration
  • Stream Processing
  • Ruby On Rails
  • Microservices Tools
Website trycelery.com
Pricing URL Official Celery Pricing
Details $-
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Apache Spark

Categories
  • Databases
  • Big Data
  • Big Data Analytics
  • Big Data Infrastructure
Website spark.apache.org
Pricing URL-
Details $
Edit details

Celery videos

+ Add

Medical Medium Anthony William on the Dos and Don’ts of Celery Juice

More videos:

  • Review - Celery Juice Review: I Drank Celery Juice for 7 Days & This Is What Happened
  • Review - CELERY JUICE REVIEW | Medical medium's celery juice for 2 months | Honest Experience | Georgia Gibbs

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 Celery and Apache Spark)

Celery

Apache Spark

Data Integration
100 100%
Data Integration
0% 0
Databases
0 0%
Databases
100% 100
Stream Processing
25 25%
Stream Processing
75% 75
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Celery and Apache Spark. 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 Celery and Apache Spark

Celery Reviews

We have no reviews of Celery yet.
Be the first one to post

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 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.

Celery mentions (0)

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

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 / 10 months ago
View more

What are some alternatives?

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

Enqueue It - Easy and scalable solution for manage and execute background tasks seamlessly in .NET applications. It allows you to schedule, queue, and process your jobs and microservices efficiently.

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

Hangfire - An easy way to perform background processing in .NET and .NET Core applications.

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

Sidekiq - Sidekiq is a simple, efficient framework for background job processing in Ruby

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

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