DBMS > LeanXcale vs. OpenQM vs. PouchDB vs. YTsaurus

System Properties Comparison LeanXcale vs. OpenQM vs. PouchDB vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

JavaScript DBMS with an API inspired by CouchDB

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Key-value store
Relational DBMS

Multivalue DBMS

Document store

Document store
Key-value store

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.11
Rank	#340	Overall
	#45	Document stores
	#50	Key-value stores

Website

www.leanxcale.com

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

pouchdb.com

ytsaurus.tech

Technical documentation

pouchdb.com/guides

ytsaurus.tech/docs/en

Developer

LeanXcale

Rocket Software, originally Martin Phillips

Apache Software Foundation

Yandex

Initial release

2015

1993

2012

2023

Current release

3.4-12

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Apache License, Version 2.0

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

C++

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

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

Ubuntu

Data scheme

yes

with some exceptions

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

via views

SQL

Support of SQL

yes

through Apache Derby

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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

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, WebSQL or LevelDB as backend

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 can be defined down to the item level

Access Control Lists

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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