DBMS > 4D vs. Bangdb vs. CockroachDB vs. Firebase Realtime Database vs. ToroDB

System Properties Comparison 4D vs. Bangdb vs. CockroachDB vs. Firebase Realtime Database vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Application development environment with integrated database management system

Converged and high performance database for device data, events, time series, document and graph

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Website

www.4d.com

bangdb.com

www.cockroachlabs.com

firebase.google.com/products/realtime-database

github.com/torodb/server

Technical documentation

developer.4d.com

docs.bangdb.com

www.cockroachlabs.com/docs

firebase.google.com/docs/database

Developer

4D, Inc

Sachin Sinha, BangDB

Cockroach Labs

Google

acquired by Google 2014

8Kdata

Initial release

1984

2012

2015

2012

2016

Current release

v20, April 2023

BangDB 2.0, October 2021

23.1.1, May 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache 2.0, commercial license available

commercial

Open Source

AGPL-V3

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, C++

Java

Server operating systems

OS X
Windows

Linux

Linux
macOS
Windows

hosted

All OS with a Java 7 VM

Data scheme

yes

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

string, integer, double, boolean, date, object_id

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

close to SQL 92

SQL like support with command line tool

yes, wire compatible with PostgreSQL

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Proprietary protocol
RESTful HTTP API

JDBC

Android
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Java
Python

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

yes

yes, Notifications (with Streaming only)

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication using RAFT

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

Users and groups

yes (enterprise version only)

Role-based access control

yes, based on authentication and database rules

Access rights for users and roles

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More resources

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