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DBMS > Cubrid vs. Drizzle vs. Google Cloud Datastore vs. Heroic vs. Kinetica

System Properties Comparison Cubrid vs. Drizzle vs. Google Cloud Datastore vs. Heroic vs. Kinetica

Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHeroic  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#189  Overall
#86  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
cloud.google.com/­datastoregithub.com/­spotify/­heroicwww.kinetica.com
Technical documentationcubrid.org/­manualscloud.google.com/­datastore/­docsspotify.github.io/­heroicdocs.kinetica.com
DeveloperCUBRID Corporation, CUBRID FoundationDrizzle project, originally started by Brian AkerGoogleSpotifyKinetica
Initial release20082008200820142012
Current release11.0, January 20217.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialOpen Source infoApache 2.0commercial
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++, JavaC++JavaC, C++
Server operating systemsLinux
Windows
FreeBSD
Linux
OS X
hostedLinux
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, 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.nononono
Secondary indexesyesyesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnousing Google App Enginenouser defined functions
Triggersyesno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication using PaxosyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
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.Eventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level

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More resources
CubridDrizzleGoogle Cloud DatastoreHeroicKinetica
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