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DBMS > Cubrid vs. Dragonfly vs. EXASOL vs. Google Cloud Datastore vs. YottaDB

System Properties Comparison Cubrid vs. Dragonfly vs. EXASOL vs. Google Cloud Datastore vs. YottaDB

Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonDragonfly  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast and solid embedded Key-value store
Primary database modelRelational DBMSKey-value storeRelational DBMSDocument storeKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitecubrid.com (korean)
cubrid.org (english)
github.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.exasol.comcloud.google.com/­datastoreyottadb.com
Technical documentationcubrid.org/­manualswww.dragonflydb.io/­docswww.exasol.com/­resourcescloud.google.com/­datastore/­docsyottadb.com/­resources/­documentation
DeveloperCUBRID Corporation, CUBRID FoundationDragonflyDB team and community contributorsExasolGoogleYottaDB, LLC
Initial release20082023200020082001
Current release11.0, January 20211.0, March 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSL 1.1commercialcommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaC++C
Server operating systemsLinux
Windows
LinuxhostedDocker
Linux
Data schemeyesscheme-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyes, details hereno
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.nonononono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLyesnoyesSQL-like query language (GQL)by using the Octo plugin
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
Proprietary protocol infoRESP - REdis Serialization Protocol.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresJava Stored ProceduresLuauser defined functionsusing Google App Engine
Triggersyespublish/subscribe channels provide some trigger functionalityyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate 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.
Foreign keys infoReferential integrityyesnoyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
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.noyesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPassword-based authenticationAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users and groups based on OS-security mechanisms

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More resources
CubridDragonflyEXASOLGoogle Cloud DatastoreYottaDB
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