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DBMS > Amazon CloudSearch vs. Apache IoTDB vs. Hyprcubd vs. MarkLogic vs. Netezza

System Properties Comparison Amazon CloudSearch vs. Apache IoTDB vs. Hyprcubd vs. MarkLogic vs. Netezza

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHyprcubd  Xexclude from comparisonMarkLogic  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkServerless Time Series DBMSOperational and transactional Enterprise NoSQL databaseData warehouse and analytics appliance part of IBM PureSystems
Primary database modelSearch engineTime Series DBMSTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­cloudsearchiotdb.apache.orghyprcubd.com (offline)www.marklogic.comwww.ibm.com/­products/­netezza
Technical documentationdocs.aws.amazon.com/­cloudsearchiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.marklogic.com
DeveloperAmazonApache Software FoundationHyprcubd, Inc.MarkLogic Corp.IBM
Initial release2012201820012000
Current release1.1.0, April 202311.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Windows
Linux infoincluded in appliance
Data schemeyesyesyesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringyesyes
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 indexesyes infoall search fields are automatically indexedyesnoyesyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageyes infoSQL92yes
APIs and other access methodsHTTP APIJDBC
Native API
gRPC (https)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
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoyesnoyes infovia XQuery or JavaScriptyes
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, with Range Indexes
User concepts infoAccess controlauthentication via encrypted signaturesyestoken accessRole-based access control at the document and subdocument levelsUsers with fine-grained authorization concept

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More resources
Amazon CloudSearchApache IoTDBHyprcubdMarkLogicNetezza infoAlso called PureData System for Analytics by IBM
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