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DBMS > etcd vs. LevelDB vs. RDF4J vs. Sequoiadb vs. Splice Machine

System Properties Comparison etcd vs. LevelDB vs. RDF4J vs. Sequoiadb vs. Splice Machine

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonLevelDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSequoiadb  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA distributed reliable key-value storeEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.NewSQL database with distributed OLTP and SQLOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeKey-value storeRDF storeDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­google/­leveldbrdf4j.orgwww.sequoiadb.comsplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
github.com/­google/­leveldb/­blob/­main/­doc/­index.mdrdf4j.org/­documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexsplicemachine.com/­how-it-works
DeveloperGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sequoiadb Ltd.Splice Machine
Initial release2011200420132014
Current release3.4, August 20191.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoServer: AGPL; Client: Apache V2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++JavaC++Java
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Illumos
Linux
OS X
Windows
Linux
OS X
Unix
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasschema-freeyes
Typing infopredefined data types such as float or datenonoyesyes infooid, date, timestamp, binary, regexyes
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 indexesnonoyesyesyes
SQL infoSupport of SQLnononoSQL-like query languageyes
APIs and other access methodsgRPC
JSON over HTTP
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
proprietary protocol using JSONJDBC
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
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
PHP
Python
.Net
C++
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesJavaScriptyes infoJava
Triggersyes, watching key changesnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShared 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.nonenoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedDocument is locked during a transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyes 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.nonoyes
User concepts infoAccess controlnononosimple password-based access controlAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdLevelDBRDF4J infoformerly known as SesameSequoiadbSplice Machine
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