DBMS > 4D vs. BigObject vs. Ignite vs. Microsoft Azure Cosmos DB vs. OushuDB

System Properties Comparison 4D vs. BigObject vs. Ignite vs. Microsoft Azure Cosmos DB vs. OushuDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for real-time computations and queries

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Globally distributed, horizontally scalable, multi-model database service

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Relational DBMS

Secondary database models

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	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

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

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

www.4d.com

bigobject.io

ignite.apache.org

azure.microsoft.com/services/cosmos-db

www.oushu.com/product/oushuDB

Technical documentation

developer.4d.com

docs.bigobject.io

apacheignite.readme.io/docs

learn.microsoft.com/azure/cosmos-db

www.oushu.com/documentation

Developer

4D, Inc

BigObject, Inc.

Apache Software Foundation

Microsoft

Oushu

Initial release

1984

2015

2014

Current release

v20, April 2023

Apache Ignite 2.6

4.0.1, August 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

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++, Java, .Net

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)

Linux
OS X
Solaris
Windows

hosted

Linux

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

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

fluentd
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++

Server-side scripts

Stored procedures

yes

Lua

yes (compute grid and cache interceptors can be used instead)

JavaScript

yes

Triggers

yes

yes (cache interceptors and events)

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes (replicated cache)

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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

User concepts

Access control

Users and groups

Security Hooks for custom implementations

Access rights can be defined down to the item level

Kerberos, SSL and role based access

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