DBMS > AlaSQL vs. Dragonfly vs. H2 vs. MaxDB vs. Microsoft SQL Server

System Properties Comparison AlaSQL vs. Dragonfly vs. H2 vs. MaxDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A robust and reliable RDBMS optimized to run all major SAP solutions

Microsofts flagship relational DBMS

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

alasql.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.h2database.com

maxdb.sap.com

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

Technical documentation

github.com/AlaSQL/alasql

www.dragonflydb.io/docs

www.h2database.com/html/main.html

maxdb.sap.com/documentation

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

Developer

Andrey Gershun & Mathias R. Wulff

DragonflyDB team and community contributors

Thomas Mueller

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Initial release

2014

2023

2005

1984

1989

Current release

1.0, March 2023

2.2.220, July 2023

7.9.10.12, February 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

BSL 1.1

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Limited community edition free

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

JavaScript

C++

Java

C++

Server operating systems

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

Linux

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

Data scheme

schema-free

scheme-free

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

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

yes

APIs and other access methods

JavaScript API

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

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

Supported programming languages

JavaScript

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Java

.Net
C#
Java
Perl
PHP
Python

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

Server-side scripts

Stored procedures

Lua

Java Stored Procedures and User-Defined Functions

yes

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

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

yes, but depending on the SQL-Server Edition

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes, multi-version concurrency control (MVCC)

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

Password-based authentication

fine grained access rights according to SQL-standard

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