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DBMS > Apache Kylin vs. GridDB vs. OpenEdge vs. TimescaleDB

System Properties Comparison Apache Kylin vs. GridDB vs. OpenEdge vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGridDB  Xexclude from comparisonOpenEdge  Xexclude from comparisonTimescaleDB  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 DataApplication development environment with integrated database management systemA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.20
Rank#175  Overall
#80  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score3.75
Rank#88  Overall
#47  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitekylin.apache.orggriddb.netwww.progress.com/­openedgewww.timescale.com
Technical documentationkylin.apache.org/­docsdocs.griddb.netdocumentation.progress.com/­output/­ua/­OpenEdge_latestdocs.timescale.com
DeveloperApache Software Foundation, originally contributed from eBay IncToshiba CorporationProgress Software CorporationTimescale
Initial release2015201319842017
Current release3.1.0, July 20205.1, August 2022OpenEdge 12.2, March 20202.13.0, November 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 availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemsLinuxLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL92, SQL-like TQL (Toshiba Query Language)yes infoclose to SQL 92yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language).Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infosince Version 11.4yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationSource-replica replication with hot standby and reads on replicas info
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 containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACID
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.noyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers and groupsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache KylinGridDBOpenEdgeTimescaleDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache KylinGridDBOpenEdgeTimescaleDB
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