DBMS > AlaSQL vs. Faircom DB vs. H2 vs. HBase vs. HyperSQL

System Properties Comparison AlaSQL vs. Faircom DB vs. H2 vs. HBase vs. HyperSQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Wide column store

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	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

alasql.org

www.faircom.com/products/faircom-db

www.h2database.com

hbase.apache.org

hsqldb.org

Technical documentation

github.com/AlaSQL/alasql

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.h2database.com/html/main.html

hbase.apache.org/book.html

hsqldb.org/web/hsqlDocsFrame.html

Developer

Andrey Gershun & Mathias R. Wulff

FairCom Corporation

Thomas Mueller

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2014

1979

2005

2008

2001

Current release

V12, November 2020

2.2.220, July 2023

2.3.4, January 2021

2.7.2, June 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Restricted, free version available

Open Source

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

Open Source

Apache version 2

Open Source

based on BSD license

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

ANSI C, C++

Java

Server operating systems

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

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

options to bring your own types, AVRO

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, ANSI SQL with proprietary extensions

yes

APIs and other access methods

JavaScript API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

JavaScript

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java Stored Procedures and User-Defined Functions

yes

Coprocessors in Java

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Immediate Consistency or 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

tunable from ACID to Eventually Consistent

ACID

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

Yes, tunable from durable to delayed durability to in-memory

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 with additional protections for files

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

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

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

HydraBase – The evolution of HBase@Facebook
5 June 2014, Facebook Engineering

HBase Tutorial
24 February 2023, Simplilearn

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

Share this page