DBMS > 4D vs. Amazon Aurora vs. BigObject vs. Microsoft Azure Cosmos DB vs. Tibero

System Properties Comparison 4D vs. Amazon Aurora vs. BigObject vs. Microsoft Azure Cosmos DB vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

MySQL and PostgreSQL compatible cloud service by Amazon

Analytic DBMS for real-time computations and queries

Globally distributed, horizontally scalable, multi-model database service

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

www.4d.com

aws.amazon.com/rds/aurora

bigobject.io

azure.microsoft.com/services/cosmos-db

us.tmaxsoft.com/products/tibero

Technical documentation

developer.4d.com

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.bigobject.io

learn.microsoft.com/azure/cosmos-db

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

4D, Inc

Amazon

BigObject, Inc.

Microsoft

TmaxSoft

Initial release

1984

2015

2014

2003

Current release

v20, April 2023

6, April 2015

License

Commercial or Open Source

commercial

free community edition available

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

C and Assembler

Server operating systems

OS X
Windows

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

4D proprietary IDE
PHP

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Lua

JavaScript

Persistent Stored Procedure (PSM)

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

planned for next version

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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