DBMS > Google Cloud Spanner vs. gStore vs. MySQL vs. UniData,UniVerse

System Properties Comparison Google Cloud Spanner vs. gStore vs. MySQL vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

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.

A native Graph DBMS to store and maintain very large RDF datasets.

Widely used open source RDBMS

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Multivalue DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

cloud.google.com/spanner

en.gstore.cn

www.mysql.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

cloud.google.com/spanner/docs

en.gstore.cn/#/enDocs

dev.mysql.com/doc

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software

Initial release

2017

2016

1995

1985

Current release

1.2, November 2023

9.0.0, July 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

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 and C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

yes

APIs and other access methods

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
SPARQL 1.1

ADO.NET
JDBC
ODBC
Proprietary native API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
PHP
Python

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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

Multi-source replication
Source-replica 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

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

Strict serializable isolation

yes

ACID

not for MyISAM storage engine

ACID

configurable

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

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Users with fine-grained authorization concept

no user groups or roles

Access rights according to SQL-standard and operating system based

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