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DBMS > EXASOL vs. Google Cloud Datastore vs. jBASE vs. RDF4J vs. Splice Machine

System Properties Comparison EXASOL vs. Google Cloud Datastore vs. jBASE vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonjBASE  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  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 robust multi-value DBMS comprising development tools and middlewareRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeMultivalue DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score1.43
Rank#160  Overall
#3  Multivalue DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.exasol.comcloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaserdf4j.orgsplicemachine.com
Technical documentationwww.exasol.com/­resourcescloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9rdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperExasolGoogleRocket Software (formerly Zumasys)Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20002008199120042014
Current release5.73.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes, details hereoptionalyesyes
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)Embedded SQL for jBASE in BASICnoyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineyesyesyes infoJava
TriggersyesCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
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
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.yesnoyesyes
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)Access rights can be defined down to the item levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
EXASOLGoogle Cloud DatastorejBASERDF4J infoformerly known as SesameSplice Machine
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