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Apache Kudu VS Hadoop

Compare Apache Kudu VS Hadoop and see what are their differences

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

Apache Kudu logo Apache Kudu

Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Apache Kudu Landing page
    Landing page //
    2021-09-26
  • Hadoop Landing page
    Landing page //
    2021-09-17

Apache Kudu videos

+ Add

Apache Kudu and Spark SQL for Fast Analytics on Fast Data (Mike Percy)

More videos:

  • Review - Apache Kudu (Incubating): New Hadoop Storage for Fast Analytics on Fast Data
  • Review - Apache Kudu: Fast Analytics on Fast Data | DataEngConf SF '16

Hadoop videos

+ Add

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 Apache Kudu and Hadoop)

Apache Kudu

Hadoop

Technical Computing
100 100%
Technical Computing
0% 0
Databases
0 0%
Databases
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Apache Kudu and Hadoop. 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 Kudu and Hadoop

Apache Kudu Reviews

We have no reviews of Apache Kudu 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.

Apache Kudu mentions (0)

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

Hadoop mentions (15)

View more

What are some alternatives?

When comparing Apache Kudu and Hadoop, you can also consider the following products

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

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

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

ATLAS.ti - ATLAS.ti is a powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data. It offers a variety of sophisticated tools for accomplishing the tasks associated with any systematic approach to "soft" data.

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

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