DBMS > LeanXcale vs. Microsoft SQL Server vs. OpenMLDB vs. OpenQM

System Properties Comparison LeanXcale vs. Microsoft SQL Server vs. OpenMLDB vs. OpenQM

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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

Microsofts flagship relational DBMS

An open-source machine learning database that provides a feature platform for training and inference

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Multivalue DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

www.leanxcale.com

www.microsoft.com/en-us/sql-server

openmldb.ai

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

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

openmldb.ai/docs/zh/main

Developer

LeanXcale

Microsoft

4 Paradigm Inc.

Rocket Software, originally Martin Phillips

Initial release

2015

1989

2020

1993

Current release

SQL Server 2022, November 2022

2024-2 February 2024

3.4-12

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java, Scala

Server operating systems

Linux
Windows

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

Fixed schema

yes

with some exceptions

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

yes

through Apache Derby

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
SQLAlchemy

Supported programming languages

C
Java
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++
Go
Java
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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