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DBMS > Cubrid vs. GBase vs. Google Cloud Datastore vs. Hazelcast vs. IBM Db2 Event Store

System Properties Comparison Cubrid vs. GBase vs. Google Cloud Datastore vs. Hazelcast vs. IBM Db2 Event Store

Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPAn analytical database for business intelligence with large customers in China.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value storeEvent Store
Time Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#169  Overall
#78  Relational DBMS
Score1.04
Rank#190  Overall
#88  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Websitecubrid.com (korean)
cubrid.org (english)
www.gbase.cncloud.google.com/­datastorehazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationcubrid.org/­manualscloud.google.com/­datastore/­docshazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperCUBRID Corporation, CUBRID FoundationGoogleHazelcastIBM
Initial release2008200820082017
Current release11.0, January 2021GBase 8a5.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaJavaC and C++
Server operating systemsLinux
Windows
hostedAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresJava Stored Proceduresusing Google App Engineyes infoEvent Listeners, Executor Servicesyes
TriggersyesCallbacks using the Google Apps Engineyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosyes infoReplicated MapActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standard

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More resources
CubridGBaseGoogle Cloud DatastoreHazelcastIBM Db2 Event Store
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