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DBMS > Amazon Neptune vs. EXASOL vs. Google Cloud Datastore vs. IRONdb vs. RDF4J

System Properties Comparison Amazon Neptune vs. EXASOL vs. Google Cloud Datastore vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA 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.
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websiteaws.amazon.com/­neptunewww.exasol.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.exasol.com/­resourcescloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperAmazonExasolGoogleCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172000200820172004
Current releaseV0.10.20, January 2018
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Java
Server operating systemshostedhostedLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infotext, numeric, histogramsyes
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 indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineyes, in Luayes
TriggersnoyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingAutomatic, metric affinity per nodenone
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 replication using Paxosconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes 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.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Amazon NeptuneEXASOLGoogle Cloud DatastoreIRONdbRDF4J infoformerly known as Sesame
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