DBMS > Badger vs. EJDB vs. Firebase Realtime Database vs. Oracle Coherence

System Properties Comparison Badger vs. EJDB vs. Firebase Realtime Database vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Oracles in-memory data grid solution

Primary database model

Key-value store

Document store

Key-value store

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

firebase.google.com/products/realtime-database

www.oracle.com/java/coherence

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/Softmotions/ejdb/blob/master/README.md

firebase.google.com/docs/database

docs.oracle.com/en/middleware/standalone/coherence

Developer

DGraph Labs

Softmotions

Google

acquired by Google 2014

Oracle

Initial release

2017

2012

2007

Current release

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

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

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

hosted

All OS with a Java VM

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

APIs and other access methods

in-process shared library

Android
iOS
JavaScript API
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
JavaScript
Objective-C

.Net
C++
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

yes

configurable

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

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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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