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Hadoop vs Redis: What are the differences?

What is Hadoop? 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.

What is Redis? An in-memory database that persists on disk. Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.

Hadoop and Redis are primarily classified as "Databases" and "In-Memory Databases" tools respectively.

"Great ecosystem" is the primary reason why developers consider Hadoop over the competitors, whereas "Performance" was stated as the key factor in picking Redis.

Hadoop and Redis are both open source tools. It seems that Redis with 37.1K GitHub stars and 14.3K forks on GitHub has more adoption than Hadoop with 9.18K GitHub stars and 5.74K GitHub forks.

reddit, Instacart, and Slack are some of the popular companies that use Redis, whereas Hadoop is used by Slack, Shopify, and SendGrid. Redis has a broader approval, being mentioned in 3239 company stacks & 1732 developers stacks; compared to Hadoop, which is listed in 237 company stacks and 116 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 Redis?

Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
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    What are some alternatives to Hadoop and Redis?
    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 Redis
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    Interest over time
    Reviews of Hadoop and Redis
    Review ofRedisRedis

    Redis is a good caching tool for a cluster, but our application had performance issues while using Aws Elasticache Redis since some page had 3000 cache hits per a page load and Redis just couldn't quickly process them all in once + latency and object deseialization time - page load took 8-9 seconds. We create a custom hybrid caching based on Redis and EhCache which worked great for our goals. Check it out on github, it's called HybriCache - https://github.com/batir-akhmerov/hybricache.

    How developers use Hadoop and Redis
    Avatar of Cloudcraft
    Cloudcraft uses RedisRedis

    Redis is used for storing all ephemeral (that's data you don't necessarily want to store permanently) user data, such as mapping of session IDs (stored in cookies) to current session variables at Cloudcraft.co. The many datastructures supported by Redis also makes it an excellent caching and realtime statistics layer. It doesn't hurt that the author, Antirez, is the nicest guy ever! These days, I would be really hard pressed to find any situation where I would pick something like Memcached over Redis.

    Avatar of Trello
    Trello uses RedisRedis

    Trello uses Redis for ephemeral data that needs to be shared between server processes but not persisted to disk. Things like the activity level of a session or a temporary OpenID key are stored in Redis, and the application is built to recover gracefully if any of these (or all of them) are lost. We run with allkeys-lru enabled and about five times as much space as its actual working set needs, so Redis automatically discards data that hasn’t been accessed lately, and reconstructs it when necessary.

    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 Stack Exchange
    Stack Exchange uses RedisRedis

    The UI has message inbox that is sent a message when you get a new badge, receive a message, significant event, etc. Done using WebSockets and is powered by redis. Redis has 2 slaves, SQL has 2 replicas, tag engine has 3 nodes, elastic has 3 nodes - any other service has high availability as well (and exists in both data centers).

    Avatar of Brandon Adams
    Brandon Adams uses RedisRedis

    Redis makes certain operations very easy. When I need a high-availability store, I typically look elsewhere, but for rapid development with the ability to land on your feet in prod, Redis is great. The available data types make it easy to build non-trivial indexes that would require complex queries in postgres.

    Avatar of Kent Steiner
    Kent Steiner uses RedisRedis

    I use Redis for cacheing, data storage, mining and augmentation, proprietary distributed event system for disparate apps and services to talk to each other, and more. Redis has some very useful native data types for tracking, slicing and dicing information.

    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 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?

    How much does Hadoop cost?
    How much does Redis cost?
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