DBMS > EJDB vs. FatDB vs. IRONdb vs. Oracle NoSQL

System Properties Comparison EJDB vs. FatDB vs. IRONdb vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store

Document store
Key-value store

Time Series DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Website

github.com/Softmotions/ejdb

www.circonus.com/solutions/time-series-database/

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Softmotions

FatCloud

Circonus LLC.

Oracle

Initial release

2012

2017

2011

Current release

V0.10.20, January 2018

23.3, December 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

Server operating systems

server-less

Windows

Linux

Linux
Solaris SPARC/x86

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

text, numeric, histograms

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

Via inetgration in SQL Server

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like DML and DDL statements

APIs and other access methods

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API

RESTful HTTP API

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

yes, in Lua

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

configurable replication factor, datacenter aware

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

depending on configuration

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

configurable

ACID within a storage node (=shard)

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.

yes

off heap cache

User concepts

Access control

Can implement custom security layer via applications

Access rights for users and roles

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