DBMS > Badger vs. Cubrid vs. DataFS vs. FileMaker

System Properties Comparison Badger vs. Cubrid vs. DataFS vs. FileMaker

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Primary database model

Secondary database models

Graph DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Website

github.com/dgraph-io/badger

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

newdatabase.com

www.claris.com/filemaker

Technical documentation

godoc.org/github.com/dgraph-io/badger

cubrid.org/manuals

dev.mobiland.com/Overview.xsp

www.claris.com/resources/documentation

Developer

DGraph Labs

CUBRID Corporation, CUBRID Foundation

Mobiland AG

Claris

a subsidiary of Apple

Initial release

2017

2008

2018

1983

Current release

11.0, January 2021

1.1.263, October 2022

19.4.1, November 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++, Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Windows

iOS

client part only
Linux
OS X
Windows

Data scheme

schema-free

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

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.

yes

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

.NET Client API
Proprietary client DLL
WinRT client

Filemaker WebDirect
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C#
C++
VB.Net

PHP

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Source-replica replication, warm standby

since Version 14

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Windows-Profile

simple rights management via user accounts and connection to external directory services

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