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DBMS > Apache Kylin vs. GridDB vs. Manticore Search vs. RDF4J

System Properties Comparison Apache Kylin vs. GridDB vs. Manticore Search vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGridDB  Xexclude from comparisonManticore Search  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackScalable in-memory time series database optimized for IoT and Big DataMulti-storage database for search, including full-text search.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSTime Series DBMSSearch engineRDF store
Secondary database modelsKey-value store
Relational DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score0.69
Rank#230  Overall
#9  RDF stores
Websitekylin.apache.orggriddb.netmanticoresearch.comrdf4j.org
Technical documentationkylin.apache.org/­docsdocs.griddb.netmanual.manticoresearch.comrdf4j.org/­documentation
DeveloperApache Software Foundation, originally contributed from eBay IncToshiba CorporationManticore SoftwareSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2015201320172004
Current release3.1.0, July 20205.1, August 20226.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2Open 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 languageJavaC++C++Java
Server operating systemsLinuxLinuxFreeBSD
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesFixed schemayes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XML
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSynchronous replication based on Galera librarynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelyes infoisolated transactions for atomic changes and binary logging for safe writesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes 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.noyes
User concepts infoAccess controlAccess rights for users can be defined per databasenono
More information provided by the system vendor
Apache KylinGridDBManticore SearchRDF4J 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 KylinGridDBManticore SearchRDF4J infoformerly known as Sesame
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