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Apache Druid VS Hadoop

Compare Apache Druid VS Hadoop and see what are their differences

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Apache Druid logo Apache Druid

Fast column-oriented distributed data store

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Apache Druid Landing page
    Landing page //
    2023-10-07
  • Hadoop Landing page
    Landing page //
    2021-09-17

Apache Druid videos

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An introduction to Apache Druid

More videos:

  • Review - Building a Real-Time Analytics Stack with Apache Kafka and Apache Druid

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 Apache Druid and Hadoop)

Apache Druid

Hadoop

Databases
44 44%
Databases
56% 56
Big Data
46 46%
Big Data
54% 54
Relational Databases
43 43%
Relational Databases
57% 57
Data Dashboard
100 100%
Data Dashboard
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Druid and Hadoop

Apache Druid Reviews

Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?
“When you're dealing with highly concurrent environments, you really need an architecture that’s designed for that CPU efficiency to get the most performance out of the smallest hardware footprint—which is another reason why folks like to use Apache Druid,” says David Wang, VP of Product and Corporate Marketing at Imply. (Imply offers Druid as a service.)
Source: embeddable.com
Apache Druid vs. Time-Series Databases
Druid is a real-time analytics database that not only incorporates architecture designs from TSDBs such as time-based partitioning and fast aggregation, but also includes ideas from search systems and data warehouses, making it a great fit for all types of event-driven data. Druid is fundamentally an OLAP engine at heart, albeit one designed for more modern, event-driven...
Source: imply.io

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 should be more popular than Apache Druid. 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 Druid mentions (9)

  • How to choose the right type of database
    Apache Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence. - Source: dev.to / 2 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in... - Source: dev.to / 3 months ago
  • Analysing Github Stars - Extracting and analyzing data from Github using Apache NiFi®, Apache Kafka® and Apache Druid®
    Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s... - Source: dev.to / over 1 year ago
  • Apache Druid® - an enterprise architect's overview
    Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications. - Source: dev.to / over 1 year ago
  • Druids by Datadog
    Datadog's product is a bit too close to Apache Druid to have named their design system so similarly. From https://druid.apache.org/ : > Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data. - Source: Hacker News / over 1 year ago
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Hadoop mentions (15)

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What are some alternatives?

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

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

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

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

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

Apache Kylin - OLAP Engine for Big Data

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

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