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

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

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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.

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

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

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

newdatabase.com

github.com/spotify/heroic

www.ibm.com/products/netezza

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

Spotify

IBM

Initial release

2016

2018

2014

2000

Current release

1.1.263, October 2022

License

Commercial or Open Source

commercial

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

Java

Server operating systems

hosted

Windows

Linux

included in appliance

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

yes

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

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

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

JDBC
ODBC
OLE DB

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
VB.Net

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Triggers

yes

no, except callback-events from server when changes happened

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

yes

Source-replica replication

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

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Alibaba Cloud upgrades AnalyticDB with vector database engine
25 July 2023, CloudTech News

Two Critical Flaws Found in Alibaba Cloud's PostgreSQL Databases
20 April 2023, The Hacker News

Accidental ‘write’ Permissions In Alibaba PostgreSQL Let Attackers Access Sensitive Data
22 April 2023, GBHackers

Two critical vulnerabilities spotted in Alibaba Cloud's PostgreSQL databases
21 April 2023, TEISS

Alibaba Cloud ignites AI innovation in Singapore with recent hackathon | KrASIA
27 March 2024, KrASIA

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

Netezza Performance Server
12 August 2020, ibm.com

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

provided by Google News

Share this page