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DBMS > Apache Impala vs. GridDB vs. Quasardb vs. RDF4J

System Properties Comparison Apache Impala vs. GridDB vs. Quasardb vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonQuasardb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataDistributed, high-performance timeseries databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRDF store
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteimpala.apache.orggriddb.netquasar.airdf4j.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netdoc.quasar.ai/­masterrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationquasardbSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013201320092004
Current release4.1.0, June 20225.1, August 20223.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++Java
Server operating systemsLinuxLinuxBSD
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infointeger and binaryyes
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.nonono
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseCryptographically strong user authentication and audit trailno
More information provided by the system vendor
Apache ImpalaGridDBQuasardbRDF4J infoformerly known as Sesame
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache ImpalaGridDBQuasardbRDF4J infoformerly known as Sesame
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