DBMS > 4D vs. BigObject vs. Ehcache vs. Kingbase vs. Microsoft Azure Cosmos DB

System Properties Comparison 4D vs. BigObject vs. Ehcache vs. Kingbase vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

azure.microsoft.com/services/cosmos-db

Technical documentation

developer.4d.com

docs.bigobject.io

www.ehcache.org/documentation

learn.microsoft.com/azure/cosmos-db

Developer

4D, Inc

BigObject, Inc.

Terracotta Inc, owned by Software AG

BeiJing KINGBASE Information technologies inc.

Microsoft

Initial release

1984

2015

2009

1999

2014

Current release

v20, April 2023

3.10.0, March 2022

V8.0, August 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses 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

Java

C and Java

Server operating systems

OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

Standard with numerous extensions

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

fluentd
ODBC
RESTful HTTP API

JCache

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

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

Supported programming languages

4D proprietary IDE
PHP

Java

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

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

Server-side scripts

Stored procedures

yes

Lua

user defined functions

JavaScript

Triggers

yes

Cache Event Listeners

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

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

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

by using Terracotta Server

yes

Implicit feature of the cloud service

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

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

yes

supports JTA and can work as an XA resource

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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