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DBMS > Netezza vs. Realm vs. Spark SQL vs. Stardog

System Properties Comparison Netezza vs. Realm vs. Spark SQL vs. Stardog

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSDocument storeRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.ibm.com/­products/­netezzarealm.iospark.apache.org/­sqlwww.stardog.com
Technical documentationrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperIBMRealm, acquired by MongoDB in May 2019Apache Software FoundationStardog-Union
Initial release2000201420142010
Current release3.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJava
Server operating systemsLinux infoincluded in applianceAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesno inforuns within the applications so server-side scripts are unnecessarynouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infoChange Listenersnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-Memory realmnoyes
User concepts infoAccess controlUsers with fine-grained authorization conceptyesnoAccess rights for users and roles

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More resources
Netezza infoAlso called PureData System for Analytics by IBMRealmSpark SQLStardog
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