DBMS > GBase vs. Microsoft Azure Synapse Analytics vs. MySQL vs. Riak KV

System Properties Comparison GBase vs. Microsoft Azure Synapse Analytics vs. MySQL vs. Riak KV

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Widely used open source RDBMS

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Key/Value like access via memcached API

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.gbase.cn

azure.microsoft.com/services/synapse-analytics

www.mysql.com

Technical documentation

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

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

Developer

General Data Technology Co., Ltd.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

OpenSource, formerly Basho Technologies

Initial release

2004

2016

1995

2009

Current release

GBase 8a, GBase 8s, GBase 8c

8.4.0, April 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2, commercial enterprise edition

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C, Java, Python

C++

C and C++

Erlang

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X

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

Secondary indexes

yes

restricted

SQL

Support of SQL

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Native Erlang Interface

Supported programming languages

C#
Java
PHP

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

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

Server-side scripts

Stored procedures

user defined functions

Transact SQL

yes

proprietary syntax

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

not for MyISAM storage engine

links between data sets can be stored

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

Users with fine-grained authorization concept

no user groups or roles

yes, using Riak Security

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.