DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. DataFS vs. Pinecone vs. STSdb vs. SWC-DB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. DataFS vs. Pinecone vs. STSdb vs. SWC-DB

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.

A managed, cloud-native vector database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Graph DBMS

Time Series 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
	#17	Object oriented DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

newdatabase.com

www.pinecone.io

github.com/STSSoft/STSdb4

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

dev.mobiland.com/Overview.xsp

docs.pinecone.io/docs/overview

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Mobiland AG

Pinecone Systems, Inc

STS Soft SC

Alex Kashirin

Initial release

2016

2018

2019

2011

2020

Current release

1.1.263, October 2022

4.0.8, September 2015

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

Open Source

GPL V3

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++

Server operating systems

hosted

Windows

hosted

Windows

Linux

Data scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

.NET Client API

Proprietary protocol
Thrift

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
VB.Net

Python

C#
Java

C++

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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