DBMS > Firebase Realtime Database vs. Spark SQL vs. SWC-DB vs. VelocityDB

System Properties Comparison Firebase Realtime Database vs. Spark SQL vs. SWC-DB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

A high performance, scalable Wide Column DBMS

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

Primary database model

Document store

Relational DBMS

Wide column store

Graph DBMS
Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

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

Website

firebase.google.com/products/realtime-database

spark.apache.org/sql

github.com/kashirin-alex/swc-db
www.swcdb.org

velocitydb.com

Technical documentation

firebase.google.com/docs/database

spark.apache.org/docs/latest/sql-programming-guide.html

velocitydb.com/UserGuide

Developer

Google

acquired by Google 2014

Apache Software Foundation

Alex Kashirin

VelocityDB Inc

Initial release

2012

2014

2020

2011

Current release

3.5.0 ( 2.13), September 2023

0.5, April 2021

7.x

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Any that supports .NET

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

Proprietary protocol
Thrift

.Net

Supported programming languages

Java
JavaScript
Objective-C

Java
Python
R
Scala

C++

.Net

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes, based on authentication and database rules

Based on Windows Authentication

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
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