DBMS > Atos Standard Common Repository vs. FileMaker vs. Firebird vs. GBase vs. GridDB

System Properties Comparison Atos Standard Common Repository vs. FileMaker vs. Firebird vs. GBase vs. GridDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Firebird is an open source RDBMS forked from Borland's InterBase

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Scalable in-memory time series database optimized for IoT and Big Data

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.claris.com/filemaker

www.firebirdsql.org

www.gbase.cn

griddb.net

Technical documentation

www.claris.com/resources/documentation

www.firebirdsql.org/en/reference-manuals

docs.griddb.net

Developer

Atos Convergence Creators

Claris

a subsidiary of Apple

Firebird Foundation

General Data Technology Co., Ltd.

Toshiba Corporation

Initial release

2016

1983

2000

As fork of Borland's InterBase

2004

2013

Current release

1703

19.4.1, November 2021

5.0.0, January 2024

GBase 8a, GBase 8s, GBase 8c

5.1, August 2022

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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

Java

C and C++

C, Java, Python

C++

Server operating systems

Linux

iOS

client part only
Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

numerical, string, blob, geometry, boolean, timestamp

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

Standard with numerous extensions

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

LDAP

Filemaker WebDirect
JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

PHP

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

PSQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

LDAP bind authentication

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

Users with fine-grained authorization concept

yes

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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.

Related products and services

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