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DBMS > Google Cloud Datastore vs. IBM Db2 Event Store vs. RDF4J vs. TinkerGraph

System Properties Comparison Google Cloud Datastore vs. IBM Db2 Event Store vs. RDF4J vs. TinkerGraph

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use casesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument storeEvent Store
Time Series DBMS
RDF storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storerdf4j.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storerdf4j.org/­documentation
DeveloperGoogleIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720042009
Current release2.0
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaJava
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Unix
Windows
Data schemeschema-freeyesyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLSQL-like query language (GQL)yes infothrough the embedded Spark runtimenono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
PHP
Python
Groovy
Java
Server-side scripts infoStored proceduresusing Google App Engineyesyesno
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosActive-active shard replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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.Eventual Consistencynone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesno
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infoin-memory storage is supported as welloptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnono

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More resources
Google Cloud DatastoreIBM Db2 Event StoreRDF4J infoformerly known as SesameTinkerGraph
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