DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Cubrid vs. Databricks vs. Transbase

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Cubrid vs. Databricks vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

cubrid.com (korean)
cubrid.org (english)

www.databricks.com

www.transaction.de/en/products/transbase.html

Technical documentation

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

cubrid.org/manuals

docs.databricks.com

www.transaction.de/en/products/transbase/features.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

CUBRID Corporation, CUBRID Foundation

Databricks

Transaction Software GmbH

Initial release

2016

2008

2013

1987

Current release

11.0, January 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free development license

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, C++, Java

C and C++

Server operating systems

hosted

Linux
Windows

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

SQL

Support of SQL

yes

with Databricks SQL

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
Perl
Python
R

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions and aggregates

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

Source-replica replication

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

yes

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

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