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DBMS > Datomic vs. Graph Engine vs. Netezza vs. Stardog

System Properties Comparison Datomic vs. Graph Engine vs. Netezza vs. Stardog

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineData warehouse and analytics appliance part of IBM PureSystemsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSGraph DBMS
Key-value store
Relational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.datomic.comwww.graphengine.iowww.ibm.com/­products/­netezzawww.stardog.com
Technical documentationdocs.datomic.comwww.graphengine.io/­docs/­manualdocs.stardog.com
DeveloperCognitectMicrosoftIBMStardog-Union
Initial release2012201020002010
Current release1.0.6735, June 20237.3.0, May 2020
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoMIT Licensecommercialcommercial 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 languageJava, Clojure.NET and CJava
Server operating systemsAll OS with a Java VM.NETLinux infoincluded in applianceLinux
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 indexesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnonoyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIJDBC
ODBC
OLE DB
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 languagesClojure
Java
C#
C++
F#
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesyesuser defined functions and aggregates, HTTP Server extensions in Java
TriggersBy using transaction functionsnonoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
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 dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptAccess rights for users and roles

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More resources
DatomicGraph Engine infoformer name: TrinityNetezza infoAlso called PureData System for Analytics by IBMStardog
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