DBMS > Blueflood vs. Firebase Realtime Database vs. TimescaleDB vs. Valentina Server

System Properties Comparison Blueflood vs. Firebase Realtime Database vs. TimescaleDB vs. Valentina Server

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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.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Object-relational database and reports server

Primary database model

Secondary database models

Relational DBMS

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

blueflood.io

firebase.google.com/products/realtime-database

www.timescale.com

www.valentina-db.net

Technical documentation

github.com/rax-maas/blueflood/wiki

firebase.google.com/docs/database

docs.timescale.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Rackspace

Google

acquired by Google 2014

Timescale

Paradigma Software

Initial release

2013

2012

2017

1999

Current release

2.15.0, May 2024

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

Linux
OS X

hosted

Linux
OS X
Windows

Data scheme

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

HTTP REST

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ODBC

Supported programming languages

Java
JavaScript
Objective-C

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication with hot standby and reads on replicas

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

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

fine grained access rights according to SQL-standard

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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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