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DBMS > etcd vs. Google Cloud Datastore vs. Kinetica vs. Oracle Berkeley DB vs. RDF4J

System Properties Comparison etcd vs. Google Cloud Datastore vs. Kinetica vs. Oracle Berkeley DB vs. RDF4J

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsWidely used in-process key-value storeRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value storeDocument storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorewww.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlrdf4j.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsdocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlrdf4j.org/­documentation
DeveloperGoogleKineticaOracle infooriginally developed by Sleepycat, which was acquired by OracleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201219942004
Current release3.4, August 20197.1, August 202118.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infocommercial license availableOpen Source infoEclipse Distribution License (EDL), v1.0.
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 languageGoC, C++C, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyes, details hereyesnoyes
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsnoyes
Triggersyes, watching key changesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using PaxosSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelnono

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More resources
etcdGoogle Cloud DatastoreKineticaOracle Berkeley DBRDF4J infoformerly known as Sesame
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