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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. Kinetica vs. RDF4J

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. Kinetica vs. RDF4J

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptunewww.kinetica.comrdf4j.org
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcesdocs.kinetica.comrdf4j.org/­documentation
DeveloperAmazonKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2019201720122004
Current release7.1, August 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Java
Server operating systemshostedhostedLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes infoRDF Schemas
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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnonouser defined functionsyes
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-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 replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and roles on table levelno

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More resources
Amazon DocumentDBAmazon NeptuneKineticaRDF4J infoformerly known as Sesame
Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services
16 April 2024, AWS Blog

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AWS announces Amazon Neptune I/O-Optimized
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14 March 2024, AWS Blog

Create a Virtual Knowledge Graph with Amazon Neptune and an Amazon S3 data lake | Amazon Web Services
21 February 2024, AWS Blog

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Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

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