DBMS > FatDB vs. FileMaker vs. Google Cloud Datastore vs. SQLite vs. Yaacomo

System Properties Comparison FatDB vs. FileMaker vs. Google Cloud Datastore vs. SQLite vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Widely used embeddable, in-process RDBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.claris.com/filemaker

cloud.google.com/datastore

www.sqlite.org

yaacomo.com

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/datastore/docs

www.sqlite.org/docs.html

Developer

FatCloud

Claris

a subsidiary of Apple

Google

Dwayne Richard Hipp

Q2WEB GmbH

Initial release

2012

1983

2008

2000

2009

Current release

19.4.1, November 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Public Domain

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

Server operating systems

Windows

iOS

client part only
Linux
OS X
Windows

hosted

server-less

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

not rigid because of 'dynamic typing' concept.

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

Via inetgration in SQL Server

yes

via plugins

SQL-like query language (GQL)

yes

SQL-92 is not fully supported

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Filemaker WebDirect
JDBC
ODBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC

Supported programming languages

PHP

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

via applications

yes

using Google App Engine

Triggers

yes

via applications

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication, warm standby

since Version 14

Multi-source replication using Paxos

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Can implement custom security layer via applications

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)

fine grained access rights according to SQL-standard

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