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DBMS > Amazon Neptune vs. Splice Machine vs. Stardog vs. Valentina Server

System Properties Comparison Amazon Neptune vs. Splice Machine vs. Stardog vs. Valentina Server

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationObject-relational database and reports server
Primary database modelGraph DBMS
RDF store
Relational DBMSGraph DBMS
RDF store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websiteaws.amazon.com/­neptunesplicemachine.comwww.stardog.comwww.valentina-db.net
Technical documentationaws.amazon.com/­neptune/­developer-resourcessplicemachine.com/­how-it-worksdocs.stardog.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAmazonSplice MachineStardog-UnionParadigma Software
Initial release2017201420101999
Current release3.1, March 20217.3.0, May 20205.7.5
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportyes
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.nono infoImport/export of XML data possible
Secondary indexesnoyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLnoyesYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoyes infoJavauser defined functions and aggregates, HTTP Server extensions in Javayes
Triggersnoyesyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source replication
Source-replica replication
Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Amazon NeptuneSplice MachineStardogValentina Server
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