DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Atos Standard Common Repository vs. GBase vs. Riak TS vs. Spark SQL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Atos Standard Common Repository vs. GBase vs. Riak TS vs. Spark SQL

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series 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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

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

www.gbase.cn

spark.apache.org/sql

Technical documentation

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

www.tiot.jp/riak-docs/riak/ts/latest

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Atos Convergence Creators

General Data Technology Co., Ltd.

Open Source, formerly Basho Technologies

Apache Software Foundation

Initial release

2016

2004

2015

2014

Current release

1703

GBase 8a, GBase 8s, GBase 8c

3.0.0, September 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, Java, Python

Erlang

Scala

Server operating systems

hosted

Linux

Linux
OS X

Linux
OS X
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

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

restricted

SQL

Support of SQL

yes

Standard with numerous extensions

yes, limited

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

LDAP

ADO.NET
C API
JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

All languages with LDAP bindings

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

cell division

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Atomic execution of specific operations

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

LDAP bind authentication

yes

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