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DBMS > etcd vs. Hazelcast vs. RDF4J vs. Sadas Engine vs. Spark SQL

System Properties Comparison etcd vs. Hazelcast vs. RDF4J vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonHazelcast  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeA widely adopted in-memory data gridRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value storeRDF storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
hazelcast.comrdf4j.orgwww.sadasengine.comspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hazelcast.org/­imdg/­docsrdf4j.org/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHazelcastSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SADAS s.r.l.Apache Software Foundation
Initial release2008200420062014
Current release3.4, August 20195.3.6, November 20238.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoEclipse Distribution License (EDL), v1.0.commercial infofree trial version availableOpen Source infoApache 2.0
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 languageGoJavaJavaC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMLinux
OS X
Unix
Windows
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.noyes infothe object must implement a serialization strategynono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL-like query languagenoyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
PHP
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyesnono
Triggersyes, watching key changesyes infoEventsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoReplicated Mapnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedACID infoIsolation support depends on the API usedno
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.noyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoRole-based access controlnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
etcdHazelcastRDF4J infoformerly known as SesameSadas EngineSpark SQL
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