DBMS > AlaSQL vs. Ehcache vs. H2 vs. HBase vs. Linter

System Properties Comparison AlaSQL vs. Ehcache vs. H2 vs. HBase vs. Linter

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A widely adopted Java cache with tiered storage options

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

RDBMS for high security requirements

Primary database model

Document store
Relational DBMS

Secondary database models

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	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

www.ehcache.org/documentation

www.h2database.com/html/main.html

hbase.apache.org/book.html

Developer

Andrey Gershun & Mathias R. Wulff

Terracotta Inc, owned by Software AG

Thomas Mueller

Apache Software Foundation

Apache top-level project, originally developed by Powerset

relex.ru

Initial release

2014

2009

2005

2008

1990

Current release

3.10.0, March 2022

2.2.220, July 2023

2.3.4, January 2021

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; commercial licenses available

Open Source

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

Open Source

Apache version 2

commercial

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 and C++

Server operating systems

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

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

schema-free

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

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

APIs and other access methods

JavaScript API

JCache

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Coprocessors in Java

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

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

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

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

yes

supports JTA and can work as an XA resource

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

using a tiered cache-storage approach

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

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

fine grained access rights according to SQL-standard

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