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Dremio VS Hadoop

Compare Dremio VS Hadoop and see what are their differences

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

Dremio logo Dremio

Get more value from your data, faster. Dremio makes your data engineers more productive, and your data consumers more self-sufficient.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Dremio Landing page
    Landing page //
    2023-08-27
  • Hadoop Landing page
    Landing page //
    2021-09-17

Dremio videos

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Introduction to Self-Service Data with Dremio

More videos:

  • Review - Data Access for Data Science | Dremio
  • Demo - Dremio Demo | Deploying Dremio AWS Edition Step-by-Step

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 Dremio and Hadoop)

Dremio

Hadoop

Office & Productivity
100 100%
Office & Productivity
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 Dremio 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 Dremio and Hadoop

Dremio Reviews

We have no reviews of Dremio 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.

Dremio mentions (0)

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

Hadoop mentions (15)

View more

What are some alternatives?

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

Zaloni Data Platform - Get self-service data from a platform that accelerates business insights. Use data from any source, anywhere: the cloud, on-premises, multi-cloud or hybrid.

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

Mozart Data - The easiest way for teams to build a Modern Data Stack

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

Minitab Connect - Minitab Connect is a data management platform that comes with cloud-based data and integration workflows having data governance and integration tools.

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

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