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MapR Converged Data Platform VS Hadoop

Compare MapR Converged Data Platform VS Hadoop and see what are their differences

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

MapR Converged Data Platform logo MapR Converged Data Platform

An enterprise-grade distributed data platform that you can trust to reliably store and process big and fast data.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • MapR Converged Data Platform Landing page
    Landing page //
    2022-10-08
  • Hadoop Landing page
    Landing page //
    2021-09-17

MapR Converged Data Platform videos

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Lab Video Summary - MapR Converged Data Platform with MapR Streams

Hadoop videos

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What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Category Popularity

0-100% (relative to MapR Converged Data Platform and Hadoop)

MapR Converged Data Platform

Hadoop

Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
0 0%
Databases
100% 100
Development
100 100%
Development
0% 0
Big Data
27 27%
Big Data
73% 73

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare MapR Converged Data Platform and Hadoop

MapR Converged Data Platform Reviews

We have no reviews of MapR Converged Data Platform yet.
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Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
Source: www.datacamp.com
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
Source: www.analytixlabs.co.in
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Hadoop seems to be more popular. It has been mentiond 15 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.

MapR Converged Data Platform mentions (0)

We have not tracked any mentions of MapR Converged Data Platform yet. Tracking of MapR Converged Data Platform recommendations started around Mar 2021.

Hadoop mentions (15)

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What are some alternatives?

When comparing MapR Converged Data Platform and Hadoop, you can also consider the following products

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

SingleStore - SingleStore DB is a high-performance SQL compliant relational database management tool that offers data processing, ingesting, and transaction processing.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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

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