DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. DolphinDB vs. Drizzle vs. Ingres vs. Microsoft Azure Cosmos DB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. DolphinDB vs. Drizzle vs. Ingres vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Well established RDBMS

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

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

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.dolphindb.com

www.actian.com/databases/ingres

azure.microsoft.com/services/cosmos-db

Technical documentation

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

docs.dolphindb.cn/en/help200/index.html

docs.actian.com/ingres

learn.microsoft.com/azure/cosmos-db

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

DolphinDB, Inc

Drizzle project, originally started by Brian Aker

Actian Corporation

Microsoft

Initial release

2016

2018

2008

1974

originally developed at University Berkely in early 1970s

2014

Current release

v2.00.4, January 2022

7.2.4, September 2012

11.2, May 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

GNU GPL

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
OS X

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

Supported programming languages

C
Java
Perl
Python
R

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Java
PHP

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

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

hooks for callbacks inside the server can be used.

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

Ingres Replicator

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators, Users, Groups

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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