DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. DataFS vs. FatDB vs. Heroic

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. DataFS vs. FatDB vs. Heroic

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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

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Relational DBMS

Object oriented DBMS

Document store
Key-value store

Time Series DBMS

Secondary database models

Graph DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

newdatabase.com

github.com/spotify/heroic

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

dev.mobiland.com/Overview.xsp

spotify.github.io/heroic

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Mobiland AG

FatCloud

Spotify

Initial release

2016

2018

2012

2014

Current release

1.1.263, October 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

hosted

Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Typing

predefined data types such as float or date

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

via Elasticsearch

SQL

Support of SQL

yes

Via inetgration in SQL Server

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
VB.Net

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

no, except callback-events from server when changes happened

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Windows-Profile

Can implement custom security layer via applications

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More resources

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