Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase vs Couchbase vs Hypertable vs ElasticSearch vs Accumulo vs VoltDB vs Scalaris comparison :: Software architect Kristof Kovacs. While SQL databases are insanely useful tools, their monopoly in the last decades is coming to an end. And it's just time: I can't even count the things that were forced into relational databases, but never really fitted them. (That being said, relational databases will always be the best for the stuff that has relations.) But, the differences between NoSQL databases are much bigger than ever was between one SQL database and another. This means that it is a bigger responsibility on software architects to choose the appropriate one for a project right at the beginning.
In this light, here is a comparison of Open Source NOSQL databases: The most popular ones # Redis # Best used: For rapidly changing data with a foreseeable database size (should fit mostly in memory). For example: To store real-time stock prices. Cassandra # Best used: When you need to store data so huge that it doesn't fit on server, but still want a friendly familiar interface to it.
MongoDB # ElasticSearch # CouchDB # Accumulo # Apache Accumulo. Bigtable: système de bases de données distribué version Google | InZeCloud.Fr. Aspirer l’intégralité du Net comme le fait Google et l’indexer – afin de satisfaire plus d’un milliard de requêtes par jours – nécessite un système d’accès aux données capable de trouver une information rapidement dans une volumétrie considérable.
Contrainte supplémentaire, les temps de réponse doivent être très rapides pour ne pas éveiller l’impatience des internautes. Les SGBDR traditionnelles ne suffisent plus pour satisfaire de tels besoins: les temps de réponses deviennent trop important sur de telles volumétries (on parle ici de Petabytes ). Chez Google, la réponse s’intitule Bigtable . Il s’agit d’un système de base de données distribué, compressé et à haute performance de type NoSQL .
Le développement a débuté en 2004 et la mise en production courant 2005. Le modèle de donnée Un enregistrement dans Bigtable est une sorte de carte triée distribué et multidimensionnelle. Cet exemple représente une structure d’enregistrement de la table Webtable, qui sert à référencer les pages Web. Research Publication: BigTable. Bigtable: A Distributed Storage System for Structured Data Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber Abstract Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance.
These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). To appear in: OSDI'06: Seventh Symposium on Operating System Design and Implementation, Seattle, WA, November, 2006. Download: PDF Version.
The Apache Cassandra Project. HBase - Apache HBase Home. HBase vs Cassandra. Une introduction à HBase. Home | Hypertable - Big Data. Big Performance.