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DBMS > Hive vs. IRONdb vs. Solr vs. Trafodion

System Properties Comparison Hive vs. IRONdb vs. Solr vs. Trafodion

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonSolr  Xexclude from comparisonTrafodion  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA widely used distributed, scalable search engine based on Apache LuceneTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/solr.apache.orgtrafodion.apache.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedsolr.apache.org/­resources.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release2012201720062014
Current release3.1.3, April 2022V0.10.20, January 20189.6.1, May 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaC++, Java
Server operating systemsAll OS with a Java VMLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes 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.noyesno
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)Solr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in LuaJava pluginsJava Stored Procedures
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareyesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic 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.noyesno
User concepts infoAccess controlAccess rights for users, groups and rolesnoyesfine grained access rights according to SQL-standard

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More resources
HiveIRONdbSolrTrafodion
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