DBMS > DataFS vs. Datomic vs. Faircom EDGE vs. Oracle NoSQL vs. Yanza

System Properties Comparison DataFS vs. Datomic vs. Faircom EDGE vs. Oracle NoSQL vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Time Series DBMS for IoT Applications

Primary database model

Object oriented DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

newdatabase.com

www.datomic.com

www.faircom.com/products/faircom-edge

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

yanza.com

Technical documentation

dev.mobiland.com/Overview.xsp

docs.datomic.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

Developer

Mobiland AG

Cognitect

FairCom Corporation

Oracle

Yanza

Initial release

2018

2012

1979

2011

2015

Current release

1.1.263, October 2022

1.0.6735, June 2023

V3, October 2020

23.3, December 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Restricted, free version available

Open Source

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

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Clojure

ANSI C, C++

Java

Server operating systems

Windows

All OS with a Java VM

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Solaris SPARC/x86

Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Flexible Schema (defined schema, partial schema, schema free)

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

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like DML and DDL statements

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

Clojure
Java

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

.Net, JavaScript, C/C++

Triggers

no, except callback-events from server when changes happened

By using transaction functions

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

But extensive use of caching in the application peers

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Synchronous and asynchronous realtime replication based on transaction logs

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

off heap cache

User concepts

Access control

Windows-Profile

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users and roles

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