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DBMS > Hypertable vs. Ignite vs. Solr vs. Trafodion

System Properties Comparison Hypertable vs. Ignite vs. Solr vs. Trafodion

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonIgnite  Xexclude from comparisonSolr  Xexclude from comparisonTrafodion  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as 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 LuceneTransactional SQL-on-Hadoop DBMS
Primary database modelWide column storeKey-value store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteignite.apache.orgsolr.apache.orgtrafodion.apache.org
Technical documentationapacheignite.readme.io/­docssolr.apache.org/­resources.htmltrafodion.apache.org/­documentation.html
DeveloperHypertable Inc.Apache Software FoundationApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2009201520062014
Current release0.9.8.11, March 2016Apache Ignite 2.69.6.0, April 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0Open 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java, .NetJavaC++, Java
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
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 schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyesyes 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 indexesrestricted infoonly exact value or prefix value scansyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interfaceyes
APIs and other access methodsC++ API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
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
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)Java pluginsJava Stored Procedures
Triggersnoyes (cache interceptors and events)yes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyes (replicated cache)yesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)spark-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 systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 controlnoSecurity Hooks for custom implementationsyesfine grained access rights according to SQL-standard

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HypertableIgniteSolrTrafodion
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