DBMS > Cachelot.io vs. Firebase Realtime Database vs. Tkrzw vs. UniData,UniVerse

System Properties Comparison Cachelot.io vs. Firebase Realtime Database vs. Tkrzw vs. UniData,UniVerse

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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.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

cachelot.io

firebase.google.com/products/realtime-database

dbmx.net/tkrzw

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

firebase.google.com/docs/database

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

acquired by Google 2014

Mikio Hirabayashi

Rocket Software

Initial release

2015

2012

2020

1985

Current release

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache Version 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

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

optional

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

yes

APIs and other access methods

Memcached protocol

Android
iOS
JavaScript API
RESTful HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

Java
JavaScript
Objective-C

C++
Java
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

configurable

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

using specific database classes

User concepts

Access control

yes, based on authentication and database rules

Access rights according to SQL-standard and operating system based

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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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