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DBMS > etcd vs. Google Cloud Datastore vs. Kinetica vs. RDF4J vs. Splice Machine

System Properties Comparison etcd vs. Google Cloud Datastore vs. Kinetica vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  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 CPUsRDF4J 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 Spark
Primary database modelKey-value storeDocument storeRelational DBMSRDF storeRelational DBMS
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
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorewww.kinetica.comrdf4j.orgsplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release2008201220042014
Current release3.4, August 20197.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
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++JavaJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or datenoyes, 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 indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsnoyes
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
JDBC
Native Spark Datasource
ODBC
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
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsyesyes infoJava
Triggersyes, watching key changesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
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 replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
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 configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.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 levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdGoogle Cloud DatastoreKineticaRDF4J infoformerly known as SesameSplice Machine
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