DBMS > Cachelot.io vs. Firebase Realtime Database vs. Firebolt vs. Riak KV

System Properties Comparison Cachelot.io vs. Firebase Realtime Database vs. Firebolt vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

cachelot.io

firebase.google.com/products/realtime-database

www.firebolt.io

Technical documentation

firebase.google.com/docs/database

docs.firebolt.io

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Google

acquired by Google 2014

Firebolt Analytics Inc.

OpenSource, formerly Basho Technologies

Initial release

2015

2012

2020

2009

Current release

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache version 2, commercial enterprise edition

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++

Erlang

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
OS X

Data scheme

schema-free

yes

schema-free

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

restricted

SQL

Support of SQL

yes

APIs and other access methods

Memcached protocol

Android
iOS
JavaScript API
RESTful HTTP API

.Net
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

Go
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Erlang

Triggers

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

yes, using Riak Security

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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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