DBMS > EXASOL vs. LeanXcale vs. LevelDB vs. Microsoft SQL Server

System Properties Comparison EXASOL vs. LeanXcale vs. LevelDB vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.exasol.com

www.leanxcale.com

github.com/google/leveldb

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

Technical documentation

www.exasol.com/resources

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

Exasol

LeanXcale

Google

Microsoft

Initial release

2000

2015

2011

1989

Current release

1.23, February 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

restricted free version is 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++

Server operating systems

Illumos
Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

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

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

Supported programming languages

Java
Lua
Python
R

C
Java
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

with automatic compression on writes

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 for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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