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DBMS > Ehcache vs. etcd vs. Spark SQL vs. SWC-DB

System Properties Comparison Ehcache vs. etcd vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonetcd  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA distributed reliable key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelKey-value storeKey-value storeRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score7.03
Rank#54  Overall
#5  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitewww.ehcache.orgetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationwww.ehcache.org/­documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGApache Software FoundationAlex Kashirin
Initial release200920142020
Current release3.10.0, March 20223.4, August 20193.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoScalaC++
Server operating systemsAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyes
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 indexesnonono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJCachegRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesJava.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnononono
Triggersyes infoCache Event Listenersyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serveryes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlnonono

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More resources
EhcacheetcdSpark SQLSWC-DB infoSuper Wide Column Database
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