DBMS > FileMaker vs. FoundationDB vs. GBase vs. GridDB vs. MongoDB

System Properties Comparison FileMaker vs. FoundationDB vs. GBase vs. GridDB vs. MongoDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Ordered key-value store. Core features are complimented by layers.

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

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

www.claris.com/filemaker

github.com/apple/foundationdb

www.gbase.cn

griddb.net

www.mongodb.com

Technical documentation

www.claris.com/resources/documentation

apple.github.io/foundationdb

docs.griddb.net

www.mongodb.com/docs/manual

Developer

Claris

a subsidiary of Apple

FoundationDB

General Data Technology Co., Ltd.

Toshiba Corporation

MongoDB, Inc

Initial release

1983

2013

2004

2013

2009

Current release

19.4.1, November 2021

6.2.28, November 2020

GBase 8a, GBase 8s, GBase 8c

5.1, August 2022

6.0.7, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

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

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

C++

C, Java, Python

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

Typing

predefined data types such as float or date

yes

some layers support typing

yes

numerical, string, blob, geometry, boolean, timestamp

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

supported in specific SQL layer only

Standard with numerous extensions

SQL92, SQL-like TQL (Toshiba Query Language)

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

PHP

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

yes

in SQL-layer only

user defined functions

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

yes

Source-replica replication

Multi-Source deployments with MongoDB Atlas Global Clusters
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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

ACID at container level

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

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

yes

Access rights for users can be defined per database

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

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

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

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

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Key customers

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

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

GitHub trending repository
» more

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

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

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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