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DBMS > Databricks vs. Elasticsearch vs. Hive vs. Kinetica vs. RDF4J

System Properties Comparison Databricks vs. Elasticsearch vs. Hive vs. Kinetica vs. RDF4J

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonElasticsearch  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.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 metricdata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Relational DBMS
Search engineRelational DBMSRelational DBMSRDF store
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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.databricks.comwww.elastic.co/­elasticsearchhive.apache.orgwww.kinetica.comrdf4j.org
Technical documentationdocs.databricks.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comrdf4j.org/­documentation
DeveloperDatabricksElasticApache Software Foundation infoinitially developed by FacebookKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20132010201220122004
Current release8.6, January 20233.1.3, April 20227.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicenseOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC, C++Java
Server operating systemshostedAll OS with a Java VMAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesPython
R
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes infouser defined functions and integration of map-reduceuser defined functionsyes
Triggersyes infoby using the 'percolation' featurenoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryes infoquery execution via MapReducenono
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, allEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
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 RAM
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles on table levelno
More information provided by the system vendor
DatabricksElasticsearchHiveKineticaRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksElasticsearchHiveKineticaRDF4J infoformerly known as Sesame
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