DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Atos Standard Common Repository vs. Google Cloud Spanner vs. HyperSQL vs. MySQL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Atos Standard Common Repository vs. Google Cloud Spanner vs. HyperSQL vs. MySQL

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used open source RDBMS

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

atos.net/en/convergence-creators/portfolio/standard-common-repository

cloud.google.com/spanner

hsqldb.org

www.mysql.com

Technical documentation

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

cloud.google.com/spanner/docs

hsqldb.org/web/hsqlDocsFrame.html

dev.mysql.com/doc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Atos Convergence Creators

Google

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2017

2001

1995

Current release

1703

2.7.2, June 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Server operating systems

hosted

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

yes

optional

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

Query statements complying to ANSI 2011

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

LDAP

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
Perl
Python
R

All languages with LDAP bindings

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java, SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

cell division

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication with 3 replicas for regional instances.

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Strict serializable isolation

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

LDAP bind authentication

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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