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DBMS > Drizzle vs. Elasticsearch vs. Spark SQL

System Properties Comparison Drizzle vs. Elasticsearch vs. Spark SQL

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonElasticsearch  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A 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 metricSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.elastic.co/­elasticsearchspark.apache.org/­sql
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerElasticApache Software Foundation
Initial release200820102014
Current release7.2.4, September 20128.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoElastic LicenseOpen 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 languageC++JavaScala
Server operating systemsFreeBSD
Linux
OS X
All OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
Typing infopredefined data types such as float or dateyesyesyes
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
Secondary indexesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBCJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersno infohooks for callbacks inside the server can be used.yes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connector
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 integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno

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More resources
DrizzleElasticsearchSpark SQL
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