DBMS > AlaSQL vs. Ehcache vs. Faircom DB vs. JanusGraph vs. jBASE

System Properties Comparison AlaSQL vs. Ehcache vs. Faircom DB vs. JanusGraph vs. jBASE

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A widely adopted Java cache with tiered storage options

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Document store
Relational DBMS

Key-value store

Key-value store
Relational DBMS

Graph DBMS

Multivalue 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	4.89
Rank	#67	Overall
	#8	Key-value stores

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

alasql.org

www.ehcache.org

www.faircom.com/products/faircom-db

janusgraph.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

github.com/AlaSQL/alasql

www.ehcache.org/documentation

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

docs.janusgraph.org

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Andrey Gershun & Mathias R. Wulff

Terracotta Inc, owned by Software AG

FairCom Corporation

Linux Foundation; originally developed as Titan by Aurelius

Rocket Software (formerly Zumasys)

Initial release

2014

2009

1979

2017

1991

Current release

3.10.0, March 2022

V12, November 2020

0.6.3, February 2023

5.7

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; commercial licenses available

commercial

Restricted, free version available

Open Source

Apache 2.0

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

ANSI C, C++

Java

Server operating systems

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

All OS with a Java VM

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

easily portable to other OSs

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

optional

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, ANSI SQL with proprietary extensions

Embedded SQL for jBASE in BASIC

APIs and other access methods

JavaScript API

JCache

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

JavaScript

Java

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

Clojure
Java
Python

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

tunable from ACID to Eventually Consistent

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

using a tiered cache-storage approach

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

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

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