DBMS > BigObject vs. Cachelot.io vs. Firebase Realtime Database vs. gStore

System Properties Comparison BigObject vs. Cachelot.io vs. Firebase Realtime Database vs. gStore

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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 native Graph DBMS to store and maintain very large RDF datasets.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Document store

Graph DBMS
RDF store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Website

bigobject.io

cachelot.io

firebase.google.com/products/realtime-database

en.gstore.cn

Technical documentation

docs.bigobject.io

firebase.google.com/docs/database

en.gstore.cn/#/enDocs

Developer

BigObject, Inc.

Google

acquired by Google 2014

Initial release

2015

2012

2016

Current release

1.2, November 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Simplified BSD License

commercial

Open Source

BSD

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

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

hosted

Linux

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Memcached protocol

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
SPARQL 1.1

Supported programming languages

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

Java
JavaScript
Objective-C

C++
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Lua

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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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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