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Hadoop vs MariaDB: 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 MariaDB? An enhanced, drop-in replacement for MySQL. Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

Hadoop and MariaDB belong to "Databases" category of the tech stack.

"Great ecosystem" is the top reason why over 34 developers like Hadoop, while over 150 developers mention "Drop-in mysql replacement" as the leading cause for choosing MariaDB.

Hadoop and MariaDB are both open source tools. Hadoop with 9.26K GitHub stars and 5.78K forks on GitHub appears to be more popular than MariaDB with 2.82K GitHub stars and 864 GitHub forks.

Grooveshark, Shutterstock, and Geocodio are some of the popular companies that use MariaDB, whereas Hadoop is used by Airbnb, Uber Technologies, and Spotify. MariaDB has a broader approval, being mentioned in 496 company stacks & 461 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 MariaDB?

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
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      What are some alternatives to Hadoop and MariaDB?
      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
      Decisions about Hadoop and MariaDB
      StackShare Editors
      StackShare Editors
      MySQL
      MySQL
      MariaDB
      MariaDB

      Airbnb’s web experience is powered by a Rails monolith, called Monorail, that talks to several different Java services. MySQL databases store business data and are partitioned by functionality, with messages and calendar management, for example, stored separately from the main booking flow in their own databases.

      As traffic to the site continued growing, though, “one notable resource issue with MySQL databases [was] the increasing number of database connections from application servers.”

      Airbnb uses AWS’s Relational Database Service (RDS) to power their MySQL instances, and “RDS uses the community edition of MySQL server, which employs a one-thread-per-connection model of connection management.” With Airbnb’s scale, this meant that their databases would hit the C10K problem, which states that “there is an upper bound in the number of connections that MySQL server can accept and serve without dramatically increasing the number of threads running, which severely degrades MySQL server performance.”

      When an RDS MySQL server hits resource limits, users will have trouble connecting to the site.

      MySQL does have dynamic thread pooling, but it’s only available in the enterprise edition; AWS MySQL RDS, though, doesn’t offer this feature, meaning Airbnb didn’t have access to dynamic thread pooling out-of-the-box.

      After surveying several options, the team chose MariaDB MaxScale, which is “a MySQL database proxy that supports intelligent query routing in between client applications and a set of backend MySQL servers.”

      Instead of using the MariaDB MaxScale off-the-shelf, however, they decided to fork it and implement their own version that would include connection pooling. Other MaxScale features, like request throttling and query blocklisting were implemented as well.

      To enable horizontal scaling of the web application, the team deployed a MaxScale database proxy service in between app servers and MySQL servers. Through the service discovery system SmartStack, applications now “discover and connect to the database proxy service instead of the MySQL database,” allowing horizontal scaling to meet capacity demands.

      Additionally, new Airbnb MaxScale proxy server instances can be launched to further enable horizontal scaling.

      See more
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk
      Heroku
      Heroku
      Ruby
      Ruby
      Rails
      Rails
      Amazon RDS for PostgreSQL
      Amazon RDS for PostgreSQL
      MariaDB
      MariaDB
      Microsoft SQL Server
      Microsoft SQL Server
      Amazon RDS
      Amazon RDS
      AWS Lambda
      AWS Lambda
      Python
      Python
      Redis
      Redis
      Memcached
      Memcached
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      Amazon ElastiCache
      Amazon ElastiCache

      We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

      We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

      In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

      Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

      See more
      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
      Joshua Dean Küpper
      Joshua Dean Küpper
      CEO at Scrayos UG (haftungsbeschränkt) · | 5 upvotes · 83.1K views
      atScrayos UG (haftungsbeschränkt)Scrayos UG (haftungsbeschränkt)
      MariaDB
      MariaDB
      PostgreSQL
      PostgreSQL
      GitLab
      GitLab
      Sentry
      Sentry

      We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and @Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQLs extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.

      See more
      Interest over time
      Reviews of Hadoop and MariaDB
      Review ofMariaDBMariaDB

      MySQL was founded by Allan Larsson, Michael Widenius and David Axmark in the year 1995, 19 years ago. It was released under the name of co-founder Michael Widenius daughter, ‘My‘. This project was released under GNU General Public License as well as under certain Proprietary License. MySQL was owned by MySQL AB firm until it went into the hands of Oracle Corporation. It is written in Programming Language – C and C++ and is available for Windows, Linux, Solaris, MacOS and FreeBSD.

      In the year 2009, Michael Widenius started working on MarisDB as a fork of MySQL. In the year 2012 the bricks of nonprofit MariaDB Foundation was laid. It was named after the founder’s daughter Maria.

      MariaDB is a fork of MySQL Relational Database Management System which again is released under GNU General Public License. It is written in Programming Language – C, C++, Perl and Bash and is available for Systems Linux, Windows, Solaris, MacOS and FreeBSD.

      How developers use Hadoop and MariaDB
      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 Scrayos UG (haftungsbeschränkt)
      Scrayos UG (haftungsbeschränkt) uses MariaDBMariaDB

      Aside from Redis, we use MariaDB to store long-term information like user-data and big-data like regeneration-information for our open-world servers. We extensively use the relational aspects of MariaDB in joins, nested queries and unions.

      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 Seungkwon Park
      Seungkwon Park uses MariaDBMariaDB

      mysql보다 mariaDB가 join면에서 우수하다는 문서를 읽었습니다. 이 부분은 저의 블로그에서도 다뤘고 저의 word press 블로그는 mysql 대신 mariaDB 를 사용합니다.

      특히 limit 기능이 pagenation 처리를 할 때 너무 직관적이고 편해서 mariaDB, mysql을 사랑합니다.

      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 Ana Phi Sancho
      Ana Phi Sancho uses MariaDBMariaDB

      Introduced in computer science course.managing relational database management systems, database analytics, and for data processing

      Avatar of nrise
      nrise uses MariaDBMariaDB

      수 백만개가 넘는 태그 키워드의 자동완성을 위해서 별도의 데이터베이스를 구축하였습니다. MariaDB 는 MySQL 을 포크한 프로젝트입니다. MySQL 과의 강력한 호환성을 지니며, 큰 튜닝 없이 강력한 성능을 보장합니다.

      Avatar of Dolls Kill
      Dolls Kill uses MariaDBMariaDB

      MariaDB has allowed us to easily scale out our DB cluster. Also has better replication tools than MySQL

      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 MariaDB cost?
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