DBMS > Apache Drill vs. Faircom DB vs. Firebase Realtime Database vs. jBASE vs. VelocityDB

System Properties Comparison Apache Drill vs. Faircom DB vs. Firebase Realtime Database vs. jBASE vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A robust multi-value DBMS comprising development tools and middleware

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Document store

Multivalue DBMS

Graph DBMS
Object oriented DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

drill.apache.org

www.faircom.com/products/faircom-db

firebase.google.com/products/realtime-database

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

velocitydb.com

Technical documentation

drill.apache.org/docs

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

firebase.google.com/docs/database

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

velocitydb.com/UserGuide

Developer

Apache Software Foundation

FairCom Corporation

Google

acquired by Google 2014

Rocket Software (formerly Zumasys)

VelocityDB Inc

Initial release

2012

1979

2012

1991

2011

Current release

1.20.3, January 2023

V12, November 2020

5.7

7.x

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Restricted, free version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

Server operating systems

Linux
OS X
Windows

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

easily portable to other OSs

hosted

AIX
Linux
Windows

Any that supports .NET

Data scheme

schema-free

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

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

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

SQL SELECT statement is SQL:2003 compliant

yes, ANSI SQL with proprietary extensions

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

.Net

Supported programming languages

C++

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

Java
JavaScript
Objective-C

.Net
Basic
Jabbascript
Java

.Net

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

yes

Triggers

yes

Callbacks are triggered when data changes

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

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.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Fine grained access rights according to SQL-standard with additional protections for files

yes, based on authentication and database rules

Access rights can be defined down to the item level

Based on Windows Authentication

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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