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DBMS > OrigoDB vs. Riak KV vs. Solr vs. Spark SQL

System Properties Comparison OrigoDB vs. Riak KV vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameOrigoDB  Xexclude from comparisonRiak KV  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA fully ACID in-memory object graph databaseDistributed, fault tolerant key-value storeA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Object oriented DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteorigodb.comsolr.apache.orgspark.apache.org/­sql
Technical documentationorigodb.com/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRobert Friberg et alOpenSource, formerly Basho TechnologiesApache Software FoundationApache Software Foundation
Initial release2009 infounder the name LiveDB200920062014
Current release3.2.0, December 20229.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ErlangJavaScala
Server operating systemsLinux
Windows
Linux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateUser defined using .NET types and collectionsnoyes infosupports customizable data types and automatic typingyes
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.no infocan be achieved using .NETnoyesno
Secondary indexesyesrestrictedyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnonoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methods.NET Client API
HTTP API
LINQ
HTTP API
Native Erlang Interface
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.NetC 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
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesErlangJava pluginsno
Triggersyes infoDomain Eventsyes infopre-commit hooks and post-commit hooksyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoclient side managed; servers are not synchronizedSharding infono "single point of failure"Shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritydepending on modelno infolinks between data sets can be storednono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoWrite ahead logyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlRole based authorizationyes, using Riak Securityyesno

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More resources
OrigoDBRiak KVSolrSpark SQL
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