DBMS > Cubrid vs. Dragonfly vs. Google BigQuery

System Properties Comparison Cubrid vs. Dragonfly vs. Google BigQuery

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Large scale data warehouse service with append-only tables

Primary database model

Relational DBMS

Key-value store

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

github.com/dragonflydb/dragonfly
www.dragonflydb.io

cloud.google.com/bigquery

Technical documentation

cubrid.org/manuals

www.dragonflydb.io/docs

cloud.google.com/bigquery/docs

Developer

CUBRID Corporation, CUBRID Foundation

DragonflyDB team and community contributors

Google

Initial release

2008

2023

2010

Current release

11.0, January 2021

1.0, March 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

C++

Server operating systems

Linux
Windows

Linux

hosted

Data scheme

yes

scheme-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

Supported programming languages

C
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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Lua

user defined functions

in JavaScript

Triggers

yes

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of command blocks and scripts

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.