DBMS > FatDB vs. HyperSQL vs. Microsoft Azure Cosmos DB vs. Oracle NoSQL

System Properties Comparison FatDB vs. HyperSQL vs. Microsoft Azure Cosmos DB vs. Oracle NoSQL

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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.

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Globally distributed, horizontally scalable, multi-model database service

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

hsqldb.org

azure.microsoft.com/services/cosmos-db

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

learn.microsoft.com/azure/cosmos-db

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

Developer

FatCloud

Microsoft

Oracle

Initial release

2012

2001

2014

2011

Current release

2.7.2, June 2023

24.1, May 2024

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

JSON types

optional

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

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

HTTP API

JDBC via HTTP
JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC
Java

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

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

Java, SQL

JavaScript

Triggers

yes

via applications

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Implicit feature of the cloud service

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

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

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

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

off heap cache

User concepts

Access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights for users and roles

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