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DBMS > Hive vs. Ignite vs. Kinetica vs. Solr

System Properties Comparison Hive vs. Ignite vs. Kinetica vs. Solr

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIgnite  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Websitehive.apache.orgignite.apache.orgwww.kinetica.comsolr.apache.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docsdocs.kinetica.comsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationKineticaApache Software Foundation
Initial release2012201520122006
Current release3.1.3, April 2022Apache Ignite 2.67.1, August 20219.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, .NetC, C++Java
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.yesnoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)user defined functionsJava plugins
Triggersnoyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)nospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and rolesSecurity Hooks for custom implementationsAccess rights for users and roles on table levelyes

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HiveIgniteKineticaSolr
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