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DBMS > Amazon Neptune vs. EDB Postgres vs. Splice Machine vs. Stardog

System Properties Comparison Amazon Neptune vs. EDB Postgres vs. Splice Machine vs. Stardog

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEDB Postgres  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Open-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 virtualization
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­neptunewww.enterprisedb.comsplicemachine.comwww.stardog.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.enterprisedb.com/­docssplicemachine.com/­how-it-worksdocs.stardog.com
DeveloperAmazonEnterpriseDBSplice MachineStardog-Union
Initial release2017200520142010
Current release14, December 20213.1, March 20217.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentsOpen Source infoAGPL 3.0, commercial license availablecommercial 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 serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJava
Server operating systemshostedLinux
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeyesyesschema-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.noyes infospecific XML-type available, but no XML query functionality.no infoImport/export of XML data possible
Secondary indexesnoyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoyes infostandard with numerous extensionsyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoJavauser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoby hash, list or rangeShared 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 replicationMulti-source replication
Source-replica replication
Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes, 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.noyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
Amazon NeptuneEDB PostgresSplice MachineStardog
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