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DBMS > Badger vs. EXASOL vs. Google Cloud Datastore vs. RDF4J vs. Riak KV

System Properties Comparison Badger vs. EXASOL vs. Google Cloud Datastore vs. RDF4J vs. Riak KV

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically 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.Distributed, fault tolerant key-value store
Primary database modelKey-value storeRelational DBMSDocument storeRDF storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitegithub.com/­dgraph-io/­badgerwww.exasol.comcloud.google.com/­datastorerdf4j.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.exasol.com/­resourcescloud.google.com/­datastore/­docsrdf4j.org/­documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperDGraph LabsExasolGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.OpenSource, formerly Basho Technologies
Initial release20172000200820042009
Current release3.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaErlang
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Unix
Windows
Linux
OS X
Data schemeschema-freeyesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or datenoyesyes, details hereyesno
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.nononono
Secondary indexesnoyesyesyesrestricted
SQL infoSupport of SQLnoyesSQL-like query language (GQL)nono
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (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
HTTP API
Native Erlang Interface
Supported programming languagesGoJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnouser defined functionsusing Google App EngineyesErlang
TriggersnoyesCallbacks using the Google Apps Engineyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosnoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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.Eventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesno
User concepts infoAccess controlnoAccess 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)noyes, using Riak Security

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More resources
BadgerEXASOLGoogle Cloud DatastoreRDF4J infoformerly known as SesameRiak KV
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