DBMS > LeanXcale vs. Microsoft SQL Server vs. VelocityDB vs. YTsaurus

System Properties Comparison LeanXcale vs. Microsoft SQL Server vs. VelocityDB 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

Microsofts flagship relational DBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Document store
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

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

Website

www.leanxcale.com

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

velocitydb.com

ytsaurus.tech

Technical documentation

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

velocitydb.com/UserGuide

ytsaurus.tech/docs/en

Developer

LeanXcale

Microsoft

VelocityDB Inc

Yandex

Initial release

2015

1989

2011

2023

Current release

SQL Server 2022, November 2022

7.x

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Server operating systems

Linux
Windows

Any that supports .NET

Ubuntu

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

YQL, an SQL-based language, is supported

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)

.Net

Supported programming languages

C
Java
Scala

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

.Net

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

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

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Based on Windows Authentication

Access Control Lists

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