DBMS > Lovefield vs. mSQL vs. OpenQM vs. YDB

System Properties Comparison Lovefield vs. mSQL vs. OpenQM vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Multivalue DBMS

Document store
Relational DBMS

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

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Score	0.34
Rank	#285	Overall
	#43	Document stores
	#130	Relational DBMS

Website

google.github.io/lovefield

hughestech.com.au/products/msql

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

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

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

ydb.tech/en/docs

Developer

Google

Hughes Technologies

Rocket Software, originally Martin Phillips

Yandex

Initial release

2014

1994

1993

2019

Current release

2.1.12, February 2017

4.4, October 2021

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

GPLv2, extended commercial license available

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Server operating systems

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

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

with some exceptions

Flexible Schema (defined schema, partial schema, 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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

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

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights can be defined down to the item level

Access rights defined for Yandex Cloud users

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