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DBMS > Apache Impala vs. Netezza vs. Solr vs. Valentina Server vs. Yaacomo

System Properties Comparison Apache Impala vs. Netezza vs. Solr vs. Valentina Server vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopData warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports serverOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­netezzasolr.apache.orgwww.valentina-db.netyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlsolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMApache Software FoundationParadigma SoftwareQ2WEB GmbH
Initial release20132000200619992009
Current release4.1.0, June 20229.6.0, April 20245.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinuxLinux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Android
Linux
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesyes
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 indexesyesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSolr Parallel SQL Interfaceyesyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
ODBCJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesJava pluginsyes
Triggersnonoyes infoUser configurable commands triggered on index changesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
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 persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache ImpalaNetezza infoAlso called PureData System for Analytics by IBMSolrValentina ServerYaacomo
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