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DBMS > Amazon DocumentDB vs. GigaSpaces vs. MarkLogic vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. MarkLogic vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engine
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score6.50
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Score6.03
Rank#60  Overall
#6  Search engines
Websiteaws.amazon.com/­documentdbwww.gigaspaces.comwww.marklogic.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.gigaspaces.com/­latest/­landing.htmldocs.marklogic.comsphinxsearch.com/­docs
DeveloperGigaspaces TechnologiesMarkLogic Corp.Sphinx Technologies Inc.
Initial release2019200020012001
Current release15.5, September 202011.0, December 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++C++
Server operating systemshostedLinux
macOS
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nono infoXML can be used for describing objects metadatayes
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-99 for query and DML statementsyes infoSQL92SQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C++
Java
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesyes infovia XQuery or JavaScriptno
Triggersnoyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding 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 replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoMap-Reduce pattern can be built with XAP task executorsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyes, with Range Indexes
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlRole-based access control at the document and subdocument levelsno

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More resources
Amazon DocumentDBGigaSpacesMarkLogicSphinx
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