DBMS > EJDB vs. Firebase Realtime Database vs. Newts vs. Prometheus

System Properties Comparison EJDB vs. Firebase Realtime Database vs. Newts vs. Prometheus

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Editorial information provided by DB-Engines

Name

Description

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.

Time Series DBMS based on Cassandra

Open-source Time Series DBMS and monitoring system

Primary database model

Document store

Time Series DBMS

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

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Website

github.com/Softmotions/ejdb

firebase.google.com/products/realtime-database

opennms.github.io/newts

prometheus.io

Technical documentation

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

firebase.google.com/docs/database

github.com/OpenNMS/newts/wiki

prometheus.io/docs

Developer

Softmotions

Google

acquired by Google 2014

OpenNMS Group

Initial release

2012

2014

2015

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

server-less

hosted

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

in-process shared library

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST
Java API

RESTful HTTP/JSON API

Supported programming languages

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

Java
JavaScript
Objective-C

Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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