Why developers like Hadoop

What is Hadoop?

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets 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.

Hadoop is a tool in the Databases category of a tech stack.

Hadoop is an open source tool with 9.2K GitHub stars and 5.7K GitHub forks. Here’s a link to Hadoop's open source repository on GitHub

Who uses Hadoop?

Companies

237 companies use Hadoop in their tech stacks, including Airbnb, Uber, and Spotify.

Developers

116 developers use Hadoop.

Hadoop Integrations

Datadog, Couchbase, Apache Flink, Presto, and Apache Zeppelin are some of the popular tools that integrate with Hadoop. Here's a list of all 18 tools that integrate with Hadoop.

Why developers like Hadoop?

Here’s a list of reasons why companies and developers use Hadoop

Top Reasons

Great ecosystem

One stack to rule them all

Great load balancer

Hadoop Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Hadoop in their tech stack.

Conor Myhrvold

Tech Brand Mgr, Office of CTO at Uber · 7 months ago | 3 upvotes · 67.7K views

Uber Technologies

Kafka Manager

Kafka

GitHub

Apache Spark

Hadoop

Why we built Marmaray, an open source generic data ingestion and dispersal framework and library for Apache Hadoop :

Built and designed by our Hadoop Platform team, Marmaray is a plug-in-based framework built on top of the Hadoop ecosystem. Users can add support to ingest data from any source and disperse to any sink leveraging the use of Apache Spark . The name, Marmaray, comes from a tunnel in Turkey connecting Europe and Asia. Similarly, we envisioned Marmaray within Uber as a pipeline connecting data from any source to any sink depending on customer preference:

https://eng.uber.com/marmaray-hadoop-ingestion-open-source/

(Direct GitHub repo: https://github.com/uber/marmaray Kafka Kafka Manager )

Marmaray: An Open Source Generic Data Ingestion and Dispersal Framework and Library for Apache Hadoop | Uber Engineering Blog

John Egan

at Pinterest · 5 years ago | 1 upvotes · 6.7K views

Hadoop

The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data. Hadoop

tomelm

5 years ago | 1 upvotes · 3.1K views

Yelp

Hadoop

in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered). Hadoop

John Egan

at Pinterest · 5 years ago | 1 upvotes · 1.5K views

Hadoop

The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs... Hadoop

John Egan

at Pinterest · 5 years ago | 1 upvotes · 1.5K views

Hadoop

The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs... Hadoop

Robert Brown

Co Founder at University of Cincinnati · 3 years ago | 1 upvotes · 1.2K views

Hadoop

Importing/Exporting data, interpreting results. Possible integration with SAS Hadoop

Hadoop Alternatives & Comparisons

What are some alternatives to Hadoop?

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Splunk

Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk to search, monitor, analyze and visualize machine data.

HBase

Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.

See all alternatives

Related Comparisons