DBMS > 4D vs. FileMaker vs. Google BigQuery vs. TimesTen vs. Trafodion

System Properties Comparison 4D vs. FileMaker vs. Google BigQuery vs. TimesTen vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Application development environment with integrated database management system

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

Large scale data warehouse service with append-only tables

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.4d.com

www.claris.com/filemaker

cloud.google.com/bigquery

www.oracle.com/database/technologies/related/timesten.html

trafodion.apache.org

Technical documentation

developer.4d.com

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

docs.oracle.com/en/database/other-databases/timesten/index.html

trafodion.apache.org/documentation.html

Developer

4D, Inc

Claris

a subsidiary of Apple

Google

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Apache Software Foundation, originally developed by HP

Initial release

1984

1983

2010

1998

2014

Current release

v20, April 2023

19.4.1, November 2021

Release 22.1

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

C++, Java

Server operating systems

OS X
Windows

iOS

client part only
Linux
OS X
Windows

hosted

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Linux

Data scheme

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

close to SQL 92

yes

via plugins

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

ADO.NET
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Java
Node.js
PL/SQL
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

PL/SQL

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication, warm standby

since Version 14

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Users and groups

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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