DBMS > Firebase Realtime Database vs. Immudb vs. InfluxDB vs. OrigoDB vs. SQLite

System Properties Comparison Firebase Realtime Database vs. Immudb vs. InfluxDB vs. OrigoDB vs. SQLite

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.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

DBMS for storing time series, events and metrics

A fully ACID in-memory object graph database

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Key-value store

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

with GEO package

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/codenotary/immudb
immudb.io

www.influxdata.com/products/influxdb-overview

origodb.com

www.sqlite.org

Technical documentation

firebase.google.com/docs/database

docs.immudb.io

docs.influxdata.com/influxdb

origodb.com/docs

www.sqlite.org/docs.html

Developer

Google

acquired by Google 2014

Codenotary

Robert Friberg et al

Dwayne Richard Hipp

Initial release

2012

2020

2013

2009

under the name LiveDB

2000

Current release

1.2.3, April 2022

2.7.6, April 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Public Domain

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

Server operating systems

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
OS X

through Homebrew

Linux
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data and Strings

User defined using .NET types and collections

yes

not rigid because of 'dynamic typing' concept.

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like syntax

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

gRPC protocol
PostgreSQL wire protocol

HTTP API
JSON over UDP

.NET Client API
HTTP API
LINQ

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
JavaScript
Objective-C

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

Source-replica replication

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

depending on model

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

User concepts

Access control

yes, based on authentication and database rules

simple rights management via user accounts

Role based authorization

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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