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Couchbase
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Couchbase vs Hadoop: What are the differences?

Developers describe Couchbase as "Document-Oriented NoSQL Database". Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands. On the other hand, Hadoop is detailed 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.

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

"Flexible data model, easy scalability, extremely fast" is the top reason why over 13 developers like Couchbase, while over 34 developers mention "Great ecosystem" as the leading cause for choosing Hadoop.

Hadoop is an open source tool with 9.18K GitHub stars and 5.74K GitHub forks. Here's a link to Hadoop's open source repository on GitHub.

Slack, Shopify, and SendGrid are some of the popular companies that use Hadoop, whereas Couchbase is used by RecordSetter, Musixmatch, and Crowdpark. Hadoop has a broader approval, being mentioned in 237 company stacks & 116 developers stacks; compared to Couchbase, which is listed in 45 company stacks and 20 developer stacks.

- No public GitHub repository available -

What is Couchbase?

Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.

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.
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      What are some alternatives to Couchbase and Hadoop?
      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.
      CouchDB
      Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.
      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.
      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.
      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
      Decisions about Couchbase and Hadoop
      StackShare Editors
      StackShare Editors
      Prometheus
      Prometheus
      Chef
      Chef
      Consul
      Consul
      Memcached
      Memcached
      Hack
      Hack
      Swift
      Swift
      Hadoop
      Hadoop
      Terraform
      Terraform
      Airflow
      Airflow
      Apache Spark
      Apache Spark
      Kubernetes
      Kubernetes
      gRPC
      gRPC
      HHVM (HipHop Virtual Machine)
      HHVM (HipHop Virtual Machine)
      Presto
      Presto
      Kotlin
      Kotlin
      Apache Thrift
      Apache Thrift

      Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.

      Apps
      • Web: a mix of JavaScript/ES6 and React.
      • Desktop: And Electron to ship it as a desktop application.
      • Android: a mix of Java and Kotlin.
      • iOS: written in a mix of Objective C and Swift.
      Backend
      • The core application and the API written in PHP/Hack that runs on HHVM.
      • The data is stored in MySQL using Vitess.
      • Caching is done using Memcached and MCRouter.
      • The search service takes help from SolrCloud, with various Java services.
      • The messaging system uses WebSockets with many services in Java and Go.
      • Load balancing is done using HAproxy with Consul for configuration.
      • Most services talk to each other over gRPC,
      • Some Thrift and JSON-over-HTTP
      • Voice and video calling service was built in Elixir.
      Data warehouse
      • Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
      Etc
      See more
      Interest over time
      Reviews of Couchbase and Hadoop
      No reviews found
      How developers use Couchbase and Hadoop
      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 InsideSales.com
      InsideSales.com uses CouchbaseCouchbase

      We use Couchbase heavily in our PowerStandings platform to enable real-time analytics of agent data, as well as data storage for parts of our new Playbooks product.

      Avatar of opening.io
      opening.io uses CouchbaseCouchbase

      Main data storage. Any writes to Couchbase auto-replicate to Elasticsearch (via XDRC) and from there on propagate into the internal Jezebel pipeline via opes.

      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 Dotmetrics
      Dotmetrics uses CouchbaseCouchbase

      Real-time data interaction on 600000+ rpm.

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