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

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

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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 resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

blueflood.io

firebase.google.com/products/realtime-database

spark.apache.org/sql

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

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

Technical documentation

github.com/rax-maas/blueflood/wiki

firebase.google.com/docs/database

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

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

Developer

Rackspace

Google

acquired by Google 2014

Apache Software Foundation

Alex Kashirin

Transaction Software GmbH

Initial release

2013

2012

2014

2020

1987

Current release

3.5.0 ( 2.13), September 2023

0.5, April 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

GPL V3

commercial

free development license

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

Java

Scala

C++

C and C++

Server operating systems

Linux
OS X

hosted

Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

predefined 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

yes

APIs and other access methods

HTTP REST

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
JavaScript
Objective-C

Java
Python
R
Scala

C++

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes

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.

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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