DBMS > Firebase Realtime Database vs. Percona Server for MongoDB vs. TimescaleDB vs. VoltDB

System Properties Comparison Firebase Realtime Database vs. Percona Server for MongoDB vs. TimescaleDB vs. VoltDB

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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.

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.50
Rank	#250	Overall
	#39	Document stores

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.percona.com/mongodb/software/percona-server-for-mongodb

www.timescale.com

www.voltdb.com

Technical documentation

firebase.google.com/docs/database

docs.percona.com/percona-distribution-for-mongodb

docs.timescale.com

docs.voltdb.com

Developer

Google

acquired by Google 2014

Percona

Timescale

VoltDB Inc.

Initial release

2012

2015

2017

2010

Current release

3.4.10-2.10, November 2017

2.15.0, May 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

GPL Version 2

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++

Java, C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
OS X

for development

Data 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

only a subset of SQL 99

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

proprietary protocol using JSON

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

JavaScript

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

Java

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication with hot standby and reads on replicas

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

via In-Memory Engine

User concepts

Access control

yes, based on authentication and database rules

Access rights for users and roles

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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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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