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DBMS > Ehcache vs. etcd vs. Riak KV vs. Spark SQL

System Properties Comparison Ehcache vs. etcd vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonetcd  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA distributed reliable key-value storeDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orgetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release200920092014
Current release3.10.0, March 20223.4, August 20193.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
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 languageJavaGoErlangScala
Server operating systemsAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
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 indexesnonorestrictedno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsJCachegRPC
JSON over HTTP
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesJava.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoErlangno
Triggersyes infoCache Event Listenersyes, watching key changesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infono "single point of failure"yes, utilizing Spark Core
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.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenonono
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.yesnono
User concepts infoAccess controlnonoyes, using Riak Securityno

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EhcacheetcdRiak KVSpark SQL
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