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DBMS > Amazon DocumentDB vs. Cubrid vs. IBM Db2 Event Store vs. Netezza vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Cubrid vs. IBM Db2 Event Store vs. Netezza vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCubrid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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 OLTPDistributed Event Store optimized for Internet of Things use casesData warehouse and analytics appliance part of IBM PureSystemsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSEvent Store
Time Series DBMS
Relational DBMSSearch engine
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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbcubrid.com (korean)
cubrid.org (english)
www.ibm.com/­products/­db2-event-storewww.ibm.com/­products/­netezzasphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcescubrid.org/­manualswww.ibm.com/­docs/­en/­db2-event-storesphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationIBMIBMSphinx Technologies Inc.
Initial release20192008201720002001
Current release11.0, January 20212.03.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercialOpen 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++, JavaC and C++C++
Server operating systemshostedLinux
Windows
Linux infoLinux, macOS, Windows for the developer additionLinux infoincluded in applianceFreeBSD
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.nonono
Secondary indexesyesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesyes infothrough the embedded Spark runtimeyesSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
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#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava Stored Proceduresyesyesno
Triggersnoyesnonono
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 replicationActive-active shard replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyesno
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 operationsACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes 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-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptno

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More resources
Amazon DocumentDBCubridIBM Db2 Event StoreNetezza infoAlso called PureData System for Analytics by IBMSphinx
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