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DBMS > Amazon DocumentDB vs. EsgynDB vs. Hive vs. MonetDB vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. EsgynDB vs. Hive vs. MonetDB vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonHive  Xexclude from comparisonMonetDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodiondata warehouse software for querying and managing large distributed datasets, built on HadoopA relational database management system that stores data in columnsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.esgyn.cnhive.apache.orgwww.monetdb.orgsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcescwiki.apache.org/­confluence/­display/­Hive/­Homewww.monetdb.org/­Documentationsphinxsearch.com/­docs
DeveloperEsgynApache Software Foundation infoinitially developed by FacebookMonetDB BVSphinx Technologies Inc.
Initial release20192015201220042001
Current release3.1.3, April 2022Dec2023 (11.49), December 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoMozilla Public License 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaCC++
Server operating systemshostedLinuxAll OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyes infoSQL 2003 with some extensionsSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC/ADO.NetC++
Java
PHP
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes infouser defined functions and integration of map-reduceyes, in SQL, C, Rno
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding via remote tablesSharding 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 between multi datacentersselectable replication factornone infoSource-replica replication available in experimental statusnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes infoquery execution via MapReducenono
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 possibleyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACIDno
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.no
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users, groups and rolesfine grained access rights according to SQL-standardno

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More resources
Amazon DocumentDBEsgynDBHiveMonetDBSphinx
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