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DBMS > Amazon Neptune vs. Kinetica vs. Linter vs. Sqrrl vs. Stardog

System Properties Comparison Amazon Neptune vs. Kinetica vs. Linter vs. Sqrrl vs. Stardog

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonKinetica  Xexclude from comparisonLinter  Xexclude from comparisonSqrrl  Xexclude from comparisonStardog  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudFully vectorized database across both GPUs and CPUsRDBMS for high security requirementsAdaptable, secure NoSQL built on Apache AccumuloEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Graph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­neptunewww.kinetica.comlinter.rusqrrl.comwww.stardog.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.kinetica.comdocs.stardog.com
DeveloperAmazonKineticarelex.ruAmazon infooriginally Sqrrl Data, Inc.Stardog-Union
Initial release20172012199020122010
Current release7.1, August 20217.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial 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 serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C and C++JavaJava
Server operating systemshostedLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
LinuxLinux
macOS
Windows
Data schemeschema-freeyesyesschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono infoImport/export of XML data possible
Secondary indexesnoyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
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
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQLnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infomaking use of Hadoopnone
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.Source-replica replicationSource-replica replicationselectable replication factor infomaking use of HadoopMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and roles on table levelfine grained access rights according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Access rights for users and roles

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More resources
Amazon NeptuneKineticaLinterSqrrlStardog
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