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DBMS > Google Cloud Datastore vs. RDF4J vs. Splice Machine vs. SwayDB vs. TerarkDB

System Properties Comparison Google Cloud Datastore vs. RDF4J vs. Splice Machine vs. SwayDB vs. TerarkDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparisonSwayDB  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J 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 SparkAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeRDF storeRelational DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitecloud.google.com/­datastorerdf4j.orgsplicemachine.comswaydb.simer.augithub.com/­bytedance/­terarkdb
Technical documentationcloud.google.com/­datastore/­docsrdf4j.org/­documentationsplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice MachineSimer PlahaByteDance, originally Terark
Initial release20082004201420182016
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license availableOpen Source infoGNU Affero GPL V3.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScalaC++
Server operating systemshostedLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infoRDF Schemasyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesnono
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 indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query language (GQL)noyesnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
C++ API
Java API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Java
Kotlin
Scala
C++
Java
Server-side scripts infoStored proceduresusing Google App Engineyesyes infoJavanono
TriggersCallbacks using the Google Apps Engineyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACIDAtomic execution of operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standardnono

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More resources
Google Cloud DatastoreRDF4J infoformerly known as SesameSplice MachineSwayDBTerarkDB
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