DBMS > AlaSQL vs. H2 vs. LeanXcale vs. Machbase Neo vs. MaxDB

System Properties Comparison AlaSQL vs. H2 vs. LeanXcale vs. Machbase Neo vs. MaxDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

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

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

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	8.13
Rank	#49	Overall
	#31	Relational DBMS

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

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

www.h2database.com/html/main.html

machbase.com/dbms

maxdb.sap.com/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Thomas Mueller

LeanXcale

Machbase

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

Initial release

2014

2005

2015

2013

1984

Current release

2.2.220, July 2023

V8.0, August 2023

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

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

commercial

free test version available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Java

C++

Server operating systems

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

All OS with a Java VM

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

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.

yes

through Apache Derby

SQL-like query language

yes

APIs and other access methods

JavaScript API

JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

JavaScript

Java

C
Java
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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, 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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

HarperDB - How and Why We Built It From The Ground Up on NodeJS
28 February 2021, hackernoon.com

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Combining operational and analytical databases in a single platform
26 May 2017, Cordis News

provided by Google News

“Luxembourg is a perfect target area”: Korean accelerator exec
27 October 2022, Delano.lu

provided by Google News

SAP Content Server High Availability using Amazon EFS and SUSE | Amazon Web Services
30 December 2020, AWS Blog

SAP Aligns Mainstream Maintenance Commitments Across Its Enterprise Solutions
11 August 2020, SAP News

SIOS looks to boost SAP HANA automated replication
29 March 2023, TechTarget

Remotely Exploitable Vulnerabilities in SAP Compression Algorithms
13 May 2015, Threatpost

Your SAP HANA Cheat Sheet: Milestones, Terms and More
14 May 2012, SiliconANGLE News

provided by Google News

Share this page