DBMS > AlaSQL vs. JaguarDB vs. MonetDB vs. SAP HANA

System Properties Comparison AlaSQL vs. JaguarDB vs. MonetDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Performant, highly scalable DBMS for AI and IoT applications

A relational database management system that stores data in columns

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

alasql.org

www.jaguardb.com

www.monetdb.org

www.sap.com/products/hana.html

Technical documentation

github.com/AlaSQL/alasql

www.jaguardb.com/support.html

www.monetdb.org/Documentation

help.sap.com/hana

Developer

Andrey Gershun & Mathias R. Wulff

DataJaguar, Inc.

MonetDB BV

SAP

Initial release

2014

2015

2004

2010

Current release

3.3 July 2023

Dec2023 (11.49), December 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

GPL V3.0

Open Source

Mozilla Public License 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

the server part. Clients available in other languages

Server operating systems

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

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JavaScript API

JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes, in SQL, C, R

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

rights management via user accounts

fine grained access rights according to SQL-standard

yes

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