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DBMS > Amazon Neptune vs. CrateDB vs. RDF4J vs. Vitess

System Properties Comparison Amazon Neptune vs. CrateDB vs. RDF4J vs. Vitess

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCrateDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDistributed Database based on LuceneRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelGraph DBMS
RDF store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
RDF storeRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score0.72
Rank#222  Overall
#9  RDF stores
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­neptunecratedb.comrdf4j.orgvitess.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcescratedb.com/­docsrdf4j.org/­documentationvitess.io/­docs
DeveloperAmazonCrateSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.The Linux Foundation, PlanetScale
Initial release2017201320042013
Current release5.8.1, August 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaGo
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Unix
Windows
Docker
Linux
macOS
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemasyes
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
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes infowith proprietary extensions
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Java
PHP
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yesyes infoproprietary syntax
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
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.Configurable replication on table/partition-levelnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoIsolation support depends on the API usedACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)rights management via user accountsnoUsers with fine-grained authorization concept infono user groups or roles

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More resources
Amazon NeptuneCrateDBRDF4J infoformerly known as SesameVitess
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