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Pimcore VS Apache Spark

Compare Pimcore VS Apache Spark and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Pimcore logo Pimcore

Pimcore is an award-winning data management and customer experience management software.

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.
  • Pimcore Landing page
    Landing page //
    2022-11-26

Pimcore is an open-source software platform used by more than 110 000 companies worldwide. It offers state-of-the-art digital asset management (DAM), product information management (PIM), master data management (MDM), digital experience management (DXP/CMS), multi-channel publishing, and digital commerce. Acclaimed by analysts at Gartner and Forrester, its customers include Fortune 100 companies such as Pepsi, Sony, and Audi. The company's headquarters are in Salzburg, Austria. 
Pimcore’s consolidated platform enables organizations to manage product information, digital assets, digital commerce, and web content in a consolidated setup, thus empowering them with a single ‘trusted view’ of information and delivering a superior product experience to their customers across multiple touchpoints.
What makes Pimcore a great open-source alternative to proprietary, closed-source software is its incredible flexibility, 100% API-driven architecture, composable technology, speed-to-market, plus the momentum of 150+ global solution partners. The Pimcore Platform™ is loved by developers, agencies, and enterprises. For more information, please visit pimcore.com.

  • Apache Spark Landing page
    Landing page //
    2021-12-31

Pimcore videos

+ Add

Pimcore PIM - 2 Minute Demo

More videos:

  • Review - Pimcore, Akeneo Enterprise, Akeneo Community Edition comparison. MDM-PIM systems | kt.team
  • Review - Pimcore Features Overview

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 Pimcore and Apache Spark)

Pimcore

Apache Spark

Product Information Management
100 100%
Product Information Management
0% 0
Databases
0 0%
Databases
100% 100
Digital Asset Management
100 100%
Digital Asset Management
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Pimcore 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 Pimcore and Apache Spark

Pimcore Reviews

WordPress alternatives: Which CMS platform is the best?
To conclude, Pimcore comes out as the winner in this clash. It may still not have a more significant market share or some exclusive WordPress features and plugins, but it wins in every segment. Pimcore is perfect for large companies handling large quantities of data or having several departments work on a single website.
Source: factory.dev
List Of Top 9 Product Information Management (PIM) Software Solution To Integrate Your Product Data
Pimcore PIM software is an open source product information management. It helps you centralize and harmonize all your marketing, sales, and technical product information in a single place. It can handle any type of digital data in acquiring, managing, and sharing across multiple channels.
Source: www.mindstask.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 a lot more popular than Pimcore. While we know about 56 links to Apache Spark, we've tracked only 2 mentions of Pimcore. 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.

Pimcore mentions (2)

  • Digital Asset Management
    Also, I have Pimcore up and running on AWS as well too .. https://pimcore.com/en. Source: over 2 years ago
  • What is Pimcore?
    Pimcore, by definition, is an open-source digital experience platform with superb data management capabilities. Source: over 2 years ago

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 / 3 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 / 4 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 / 6 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 / 6 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 / 12 months ago
View more

What are some alternatives?

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

Syndigo Content Experience Hub - Content Experience Hub Your end-to-end solution to collect, create, enrich, manage, syndicate, and analyze all your digital assets, Core Marketing, and Enhanced product content. Request [...]

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

Boomi - The #1 Integration Cloud - Build Integrations anytime, anywhere with no coding required using Dell Boomi's industry leading iPaaS platform.

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

Akeneo - Akeneo is an open-source Product Information Management solution.

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

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