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DBMS > Amazon DocumentDB vs. BaseX vs. Cubrid vs. GridGain vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. BaseX vs. Cubrid vs. GridGain vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBaseX  Xexclude from comparisonCubrid  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.CUBRID is an open-source SQL-based relational database management system with object extensions for OLTPGridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeNative XML DBMSRelational DBMSKey-value store
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbbasex.orgcubrid.com (korean)
cubrid.org (english)
www.gridgain.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.basex.orgcubrid.org/­manualswww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperBaseX GmbHCUBRID Corporation, CUBRID FoundationGridGain Systems, Inc.Sphinx Technologies Inc.
Initial release20192007200820072001
Current release11.0, June 202411.0, January 2021GridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen Source infoApache Version 2.0commercialOpen 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 languageJavaC, C++, JavaJava, C++, .NetC++
Server operating systemshostedLinux
OS X
Windows
Linux
Windows
Linux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyesyesno
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 indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
ADO.NET
JDBC
ODBC
OLE DB
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes infovia eventsyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneShardingSharding 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 replicasnoneSource-replica replicationyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsmultiple readers, single writerACIDACIDno
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 rolesUsers with fine-grained authorization concept on 4 levelsfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsno

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More resources
Amazon DocumentDBBaseXCubridGridGainSphinx
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