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DBMS > Amazon DocumentDB vs. Cubrid vs. Netezza vs. Solr vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Cubrid vs. Netezza vs. Solr vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCubrid  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPData warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSRelational DBMSSearch engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbcubrid.com (korean)
cubrid.org (english)
www.ibm.com/­products/­netezzasolr.apache.orgsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcescubrid.org/­manualssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationIBMApache Software FoundationSphinx Technologies Inc.
Initial release20192008200020062001
Current release11.0, January 20219.6.1, May 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaJavaC++
Server operating systemshostedLinux
Windows
Linux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesyesSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava Stored ProceduresyesJava pluginsno
Triggersnoyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptyesno

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More resources
Amazon DocumentDBCubridNetezza infoAlso called PureData System for Analytics by IBMSolrSphinx
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