DBMS > Cubrid vs. EventStoreDB vs. Google Cloud Spanner vs. Lovefield vs. mSQL

System Properties Comparison Cubrid vs. EventStoreDB vs. Google Cloud Spanner vs. Lovefield vs. mSQL

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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.

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Event Store

Relational DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.eventstore.com

cloud.google.com/spanner

google.github.io/lovefield

hughestech.com.au/products/msql

Technical documentation

cubrid.org/manuals

developers.eventstore.com

cloud.google.com/spanner/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

CUBRID Corporation, CUBRID Foundation

Event Store Limited

Google

Hughes Technologies

Initial release

2008

2012

2017

2014

1994

Current release

11.0, January 2021

21.2, February 2021

2.1.12, February 2017

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

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++, Java

JavaScript

Server operating systems

Linux
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC (using protocol buffers) API
JDBC

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

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

none

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

none

Foreign keys

Referential integrity

yes

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

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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

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