DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. GBase vs. Postgres-XL vs. Splice Machine vs. Yanza

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. GBase vs. Postgres-XL vs. Splice Machine vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial 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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.gbase.cn

www.postgres-xl.org

splicemachine.com

yanza.com

Technical documentation

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

www.postgres-xl.org/documentation

splicemachine.com/how-it-works

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

General Data Technology Co., Ltd.

Splice Machine

Yanza

Initial release

2016

2004

2014

since 2012, originally named StormDB

2014

2015

Current release

GBase 8a, GBase 8s, GBase 8c

10 R1, October 2018

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

AGPL 3.0, commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

Java

Server operating systems

hosted

Linux

Linux
macOS

Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
Native Spark Datasource
ODBC

HTTP API

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions

yes

Java

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

yes

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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