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DBMS > Hive vs. Ignite vs. Solr vs. YDB

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

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIgnite  Xexclude from comparisonSolr  Xexclude from comparisonYDB  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.A widely used distributed, scalable search engine based on Apache LuceneA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSKey-value store
Relational DBMS
Search engineDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitehive.apache.orgignite.apache.orgsolr.apache.orggithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docssolr.apache.org/­resources.htmlydb.tech/­en/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software FoundationYandex
Initial release2012201520062019
Current release3.1.3, April 2022Apache Ignite 2.69.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetJava
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.yesyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL InterfaceSQL-like query language (YQL)
APIs and other access methodsJDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)Java pluginsno
Triggersnoyes (cache interceptors and events)yes 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)yesActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
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.yesyesno
User concepts infoAccess controlAccess rights for users, groups and rolesSecurity Hooks for custom implementationsyesAccess rights defined for Yandex Cloud users

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