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

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeSearch engineDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score135.35
Rank#7  Overall
#1  Search engines
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchwww.marklogic.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.marklogic.comsphinxsearch.com/­docs
DeveloperElasticMarkLogic Corp.Sphinx Technologies Inc.
Initial release2019201020012001
Current release8.6, January 202311.0, December 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic Licensecommercial 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 languageJavaC++C++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-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.nonoyes
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageyes infoSQL92SQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
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
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
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 infoby using the 'percolation' featureyesno
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 replicasyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectoryes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate 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 operationsnoACID 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.Memcached and Redis integrationyes, with Range Indexes
User concepts infoAccess controlAccess rights for users and rolesRole-based access control at the document and subdocument levelsno

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Amazon DocumentDBElasticsearchMarkLogicSphinx
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