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Hadoop vs Memcached: What are the differences?

Developers describe Hadoop as "Open-source software for reliable, scalable, distributed computing". 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. On the other hand, Memcached is detailed as "High-performance, distributed memory object caching system". Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

Hadoop and Memcached can be primarily classified as "Databases" tools.

"Great ecosystem" is the primary reason why developers consider Hadoop over the competitors, whereas "Fast object cache" was stated as the key factor in picking Memcached.

Hadoop and Memcached are both open source tools. It seems that Hadoop with 9.26K GitHub stars and 5.78K forks on GitHub has more adoption than Memcached with 8.99K GitHub stars and 2.6K GitHub forks.

Facebook, Instagram, and Dropbox are some of the popular companies that use Memcached, whereas Hadoop is used by Airbnb, Uber Technologies, and Spotify. Memcached has a broader approval, being mentioned in 755 company stacks & 267 developers stacks; compared to Hadoop, which is listed in 237 company stacks and 127 developer stacks.

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.

What is Memcached?

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

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      What are some alternatives to Hadoop and Memcached?
      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.
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      Decisions about Hadoop and Memcached
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      How developers use Hadoop and Memcached
      Avatar of Pinterest
      Pinterest uses HadoopHadoop

      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.

      Avatar of Yelp
      Yelp uses HadoopHadoop

      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).

      Avatar of Pinterest
      Pinterest uses HadoopHadoop

      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...

      Avatar of Reactor Digital
      Reactor Digital uses MemcachedMemcached

      As part of the cacheing system within Drupal.

      Memcached mainly took care of creating and rebuilding the REST API cache once changes had been made within Drupal.

      Avatar of Casey Smith
      Casey Smith uses MemcachedMemcached

      Distributed cache exposed through Google App Engine APIs; use to stage fresh data (incoming and recently processed) for faster access in data processing pipeline.

      Avatar of The Independent
      The Independent uses MemcachedMemcached

      Memcache caches database results and articles, reducing overall DB load and allowing seamless DB maintenance during quiet periods.

      Avatar of eXon Technologies
      eXon Technologies uses MemcachedMemcached

      Used to cache most used files for our clients. Connected with CloudFlare Railgun Optimizer.

      Avatar of Robert Brown
      Robert Brown uses HadoopHadoop

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

      Avatar of Rohith Nandakumar
      Rohith Nandakumar uses HadoopHadoop

      TBD. Good to have I think. Analytics on loads of data, recommendations?

      Avatar of ScholaNoctis
      ScholaNoctis uses MemcachedMemcached

      Memcached is used as a simple page cache across the whole application.

      How much does Hadoop cost?
      How much does Memcached cost?
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