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

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

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionHigh-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 modelRelational DBMSDocument storeTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.83
Rank#87  Overall
#44  Relational DBMS
Score4.64
Rank#68  Overall
#12  Document stores
Score0.05
Rank#315  Overall
#27  Time Series DBMS
Score0.40
Rank#219  Overall
#10  RDF stores
Websitewww.exasol.com/­en/­productscloud.google.com/­datastorewww.irondb.iordf4j.org
Technical documentationwww.exasol.com/­en/­community/­resourcescloud.google.com/­datastore/­docswww.irondb.io/­docsdocs.rdf4j.org
DeveloperExasolGoogleCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2000200820172004
Current releaseV0.10.20, January 2018
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++Java
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, 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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methods.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 languagesJava
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 proceduresuser defined functionsusing Google App Engineyes, in Luayes
TriggersyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-Master replication using Paxosconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 integrityyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono
More information provided by the system vendor
EXASOLGoogle Cloud DatastoreIRONdbRDF4J infoformerly known as Sesame
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more

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More resources
EXASOLGoogle Cloud DatastoreIRONdbRDF4J infoformerly known as Sesame
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