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DBMS > GBase vs. GridDB vs. Hazelcast vs. Kdb

System Properties Comparison GBase vs. GridDB vs. Hazelcast vs. Kdb

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Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Scalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridHigh performance Time Series DBMS
Primary database modelRelational DBMSTime Series DBMSKey-value storeTime Series DBMS
Vector DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websitewww.gbase.cngriddb.nethazelcast.comkx.com
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docscode.kx.com
DeveloperGeneral Data Technology Co., Ltd.Toshiba CorporationHazelcastKx Systems, a division of First Derivatives plc
Initial release2004201320082000 infokdb was released 2000, kdb+ in 2003
Current releaseGBase 8a, GBase 8s, GBase 8c5.1, August 20225.3.6, November 20233.6, May 2018
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availablecommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonC++Javaq
Server operating systemsLinuxLinuxAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.yesnoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes infotable attribute 'grouped'
SQL infoSupport of SQLStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like query language (q)
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesC#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes infoEvent Listeners, Executor Servicesuser defined functions
Triggersyesyesyes infoEventsyes infowith views
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelone or two-phase-commit; repeatable reads; read commitedno
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.yesyesyes
User concepts infoAccess controlyesAccess rights for users can be defined per databaseRole-based access controlrights management via user accounts
More information provided by the system vendor
GBaseGridDBHazelcastKdb
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Integrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
tick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricsGitHub trending repository
» more
kdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
upon request
» more

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GBaseGridDBHazelcastKdb
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