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DBMS > Elasticsearch vs. OrigoDB vs. Spark SQL

System Properties Comparison Elasticsearch vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.elastic.co/­elasticsearchorigodb.comspark.apache.org/­sql
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperElasticRobert Friberg et alApache Software Foundation
Initial release20102009 infounder the name LiveDB2014
Current release8.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Scala
Server operating systemsAll OS with a Java VMLinux
Windows
Linux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes
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.nono infocan be achieved using .NETno
Secondary indexesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP/JSON API
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresyesyesno
Triggersyes infoby using the 'percolation' featureyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integritynodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyesno
User concepts infoAccess controlRole based authorizationno

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More resources
ElasticsearchOrigoDBSpark SQL
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