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DBMS > Apache Druid vs. Elasticsearch vs. Kinetica vs. Memcached vs. Splice Machine

System Properties Comparison Apache Druid vs. Elasticsearch vs. Kinetica vs. Memcached vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonElasticsearch  Xexclude from comparisonKinetica  Xexclude from comparisonMemcached  Xexclude from comparisonSplice Machine  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 metricFully vectorized database across both GPUs and CPUsIn-memory key-value store, originally intended for cachingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Search engineRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitedruid.apache.orgwww.elastic.co/­elasticsearchwww.kinetica.comwww.memcached.orgsplicemachine.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.kinetica.comgithub.com/­memcached/­memcached/­wikisplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsElasticKineticaDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSplice Machine
Initial release20122010201220032014
Current release29.0.1, April 20248.6, January 20237.1, August 20211.6.27, May 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoElastic LicensecommercialOpen Source infoBSD licenseOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++CJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinuxFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
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 dateyesyesyesnoyes
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.nonono
Secondary indexesyesyes infoAll search fields are automatically indexedyesnoyes
SQL infoSupport of SQLSQL for queryingSQL-like query languageSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functionsnoyes infoJava
Triggersnoyes infoby using the 'percolation' featureyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesSource-replica replicationnone infoRepcached, a Memcached patch, provides this functionallityMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop ConnectornonoYes, via Full Spark Integration
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 Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles on table levelyes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidElasticsearchKineticaMemcachedSplice Machine
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