DBMS > AlaSQL vs. CockroachDB vs. Faircom EDGE vs. jBASE vs. Transbase

System Properties Comparison AlaSQL vs. CockroachDB vs. Faircom EDGE vs. jBASE vs. Transbase

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A robust multi-value DBMS comprising development tools and middleware

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Multivalue DBMS

Relational 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	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

alasql.org

www.cockroachlabs.com

www.faircom.com/products/faircom-edge

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

www.transaction.de/en/products/transbase.html

Technical documentation

github.com/AlaSQL/alasql

www.cockroachlabs.com/docs

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

www.transaction.de/en/products/transbase/features.html

Developer

Andrey Gershun & Mathias R. Wulff

Cockroach Labs

FairCom Corporation

Rocket Software (formerly Zumasys)

Transaction Software GmbH

Initial release

2014

2015

1979

1991

1987

Current release

23.1.1, May 2023

V3, October 2020

5.7

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0, commercial license available

commercial

Restricted, free version available

commercial

free development 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++

C and C++

Server operating systems

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

Linux
macOS
Windows

Android
Linux

ARM, x86
Raspbian
Windows

AIX
Linux
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

dynamic schema

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

optional

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, wire compatible with PostgreSQL

yes

ANSI SQL queries

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

JavaScript API

JDBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.Net
Basic
Jabbascript
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using RAFT

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

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

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

only for local storage and DOM-storage

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Role-based access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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