DBMS > DataFS vs. FileMaker vs. Google Cloud Bigtable vs. PouchDB

System Properties Comparison DataFS vs. FileMaker vs. Google Cloud Bigtable vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Object oriented DBMS

Relational DBMS

Key-value store
Wide column store

Document store

Secondary database models

Graph DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

newdatabase.com

www.claris.com/filemaker

cloud.google.com/bigtable

pouchdb.com

Technical documentation

dev.mobiland.com/Overview.xsp

www.claris.com/resources/documentation

cloud.google.com/bigtable/docs

pouchdb.com/guides

Developer

Mobiland AG

Claris

a subsidiary of Apple

Google

Apache Software Foundation

Initial release

2018

1983

2015

2012

Current release

1.1.263, October 2022

19.4.1, November 2021

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

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

JavaScript

Server operating systems

Windows

iOS

client part only
Linux
OS X
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

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

yes

schema-free

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

via views

SQL

Support of SQL

yes

via plugins

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Filemaker WebDirect
JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
C#
C++
VB.Net

PHP

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

JavaScript

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

Windows-Profile

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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