DBMS > Apache Doris vs. FatDB vs. Microsoft Azure Cosmos DB vs. Netezza vs. Prometheus

System Properties Comparison Apache Doris vs. FatDB vs. Microsoft Azure Cosmos DB vs. Netezza vs. Prometheus

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

An MPP-based analytics DBMS embracing the MySQL protocol

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

Globally distributed, horizontally scalable, multi-model database service

Data warehouse and analytics appliance part of IBM PureSystems

Open-source Time Series DBMS and monitoring system

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

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

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

doris.apache.org
github.com/apache/doris

azure.microsoft.com/services/cosmos-db

www.ibm.com/products/netezza

prometheus.io

Technical documentation

github.com/apache/doris/wiki

learn.microsoft.com/azure/cosmos-db

prometheus.io/docs

Developer

Apache Software Foundation, originally contributed from Baidu

FatCloud

Microsoft

IBM

Initial release

2017

2012

2014

2000

2015

Current release

1.2.2, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

Linux

Windows

hosted

Linux

included in appliance

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

SQL-like query language

yes

APIs and other access methods

JDBC
MySQL client

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

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

JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

Supported programming languages

Java

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

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

via applications

JavaScript

yes

Triggers

yes

via applications

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

Implicit feature of the cloud service

Source-replica replication

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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