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DBMS > Amazon Neptune vs. IRONdb vs. RDF4J vs. Riak TS vs. Spark SQL

System Properties Comparison Amazon Neptune vs. IRONdb vs. RDF4J vs. Riak TS vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRiak TS  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Time Series DBMSRDF storeTime Series DBMSRelational 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
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.circonus.com/solutions/time-series-database/rdf4j.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationwww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Open Source, formerly Basho TechnologiesApache Software Foundation
Initial release20172017200420152014
Current releaseV0.10.20, January 20183.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaErlangScala
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasschema-freeyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesnoyes
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
Secondary indexesnonoyesrestrictedno
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)noyes, limitedSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes, in LuayesErlangno
Triggersnonoyesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodenoneShardingyes, utilizing Spark Core
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 factor, datacenter awarenoneselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoIsolation support depends on the API usednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nononono

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Amazon NeptuneIRONdbRDF4J infoformerly known as SesameRiak TSSpark SQL
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