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DBMS > Google Cloud Datastore vs. IBM Db2 vs. RDF4J vs. RocksDB vs. WakandaDB

System Properties Comparison Google Cloud Datastore vs. IBM Db2 vs. RDF4J vs. RocksDB vs. WakandaDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRocksDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCommon in IBM host environments, 2 different versions for host and Windows/LinuxRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Embeddable persistent key-value store optimized for fast storage (flash and RAM)WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRDF storeKey-value storeObject oriented DBMS
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score123.05
Rank#9  Overall
#6  Relational DBMS
Score0.72
Rank#222  Overall
#9  RDF stores
Score2.84
Rank#97  Overall
#16  Key-value stores
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2rdf4j.orgrocksdb.orgwakanda.github.io
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2rdf4j.org/­documentationgithub.com/­facebook/­rocksdb/­wikiwakanda.github.io/­doc
DeveloperGoogleIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Facebook, Inc.Wakanda SAS
Initial release20081983 infohost version200420132012
Current release12.1, October 20169.4.0, June 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infofree version is availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoBSDOpen Source infoAGPLv3, extended commercial license 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 languageC and C++JavaC++C++, JavaScript
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
Linux
OS X
Unix
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyes infoRDF Schemasschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesnoyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)yesnonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
C++ API
Java API
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
Java
PHP
Python
C
C++
Go
Java
Perl
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresusing Google App Engineyesyesnoyes
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux Versionnonehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infowith separate tools (MQ, InfoSphere)noneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoIsolation support depends on the API usedyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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-standardnonoyes

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More resources
Google Cloud DatastoreIBM Db2 infoformerly named DB2 or IBM Database 2RDF4J infoformerly known as SesameRocksDBWakandaDB
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