DBMS > Faircom EDGE vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. PlanetScale

System Properties Comparison Faircom EDGE vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Globally distributed, horizontally scalable, multi-model database service

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	123.05
Rank	#9	Overall
	#6	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.ibm.com/products/db2

azure.microsoft.com/services/cosmos-db

planetscale.com

Technical documentation

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

www.ibm.com/docs/en/db2

learn.microsoft.com/azure/cosmos-db

planetscale.com/docs

Developer

FairCom Corporation

IBM

Microsoft

PlanetScale

Initial release

1979

1983

host version

2014

2020

Current release

V3, October 2020

12.1, October 2016

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

free version is available

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

ANSI C, C++

C and C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Docker
Linux
macOS

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

JSON types

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

JavaScript

yes

proprietary syntax

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

only with Windows/Unix/Linux Version

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

with separate tools (MQ, InfoSphere)

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

when using SQL

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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