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DBMS > Apache Druid vs. Elasticsearch vs. GridGain vs. Oracle Coherence vs. Spark SQL

System Properties Comparison Apache Druid vs. Elasticsearch vs. GridGain vs. Oracle Coherence vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridGain  Xexclude from comparisonOracle Coherence  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA 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 metricGridGain is an in-memory computing platform, built on Apache IgniteOracles in-memory data grid solutionSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Search engineKey-value store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.elastic.co/­elasticsearchwww.gridgain.comwww.oracle.com/­java/­coherencespark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.gridgain.com/­docs/­index.htmldocs.oracle.com/­en/­middleware/­standalone/­coherencespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsElasticGridGain Systems, Inc.OracleApache Software Foundation
Initial release20122010200720072014
Current release29.0.1, April 20248.6, January 2023GridGain 8.5.114.1, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoElastic LicensecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava, C++, .NetJavaScala
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesnono
Secondary indexesyesyes infoAll search fields are automatically indexedyesnono
SQL infoSupport of SQLSQL for queryingSQL-like query languageANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JCache
JPA
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C++
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)nono
Triggersnoyes infoby using the 'percolation' featureyes (cache interceptors and events)yes infoLive Eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes (replicated cache)yes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectoryes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDconfigurableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infooptionallyyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyesyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsauthentification to access the cache via certificates or http basic authenticationno

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More resources
Apache DruidElasticsearchGridGainOracle CoherenceSpark SQL
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