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DBMS > Apache Impala vs. BoltDB vs. Kinetica vs. OpenQM vs. Solr

System Properties Comparison Apache Impala vs. BoltDB vs. Kinetica vs. OpenQM vs. Solr

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBoltDB  Xexclude from comparisonKinetica  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embedded key-value store for Go.Fully vectorized database across both GPUs and CPUsQpenQM is a high-performance, self-tuning, multi-value DBMSA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeRelational DBMSMultivalue DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.74
Rank#220  Overall
#31  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orggithub.com/­boltdb/­boltwww.kinetica.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmsolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.kinetica.comsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKineticaRocket Software, originally Martin PhillipsApache Software Foundation
Initial release20132013201219932006
Current release4.1.0, June 20227.1, August 20213.4-129.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicensecommercialOpen Source infoGPLv2, extended commercial license availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoC, C++Java
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
LinuxAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyes infowith some exceptionsyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes 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.nononoyesyes
Secondary indexesyesnoyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCGoC++
Java
JavaScript (Node.js)
Python
.Net
Basic
C
Java
Objective C
PHP
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-reducenouser defined functionsyesJava plugins
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users and roles on table levelAccess rights can be defined down to the item levelyes

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More resources
Apache ImpalaBoltDBKineticaOpenQM infoalso called QMSolr
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