DBMS > Faircom EDGE vs. Microsoft Azure AI Search vs. Snowflake vs. Vitess

System Properties Comparison Faircom EDGE vs. Microsoft Azure AI Search vs. Snowflake vs. Vitess

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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

Search-as-a-service for web and mobile app development

Cloud-based data warehousing service for structured and semi-structured data

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store
Relational DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.faircom.com/products/faircom-edge

azure.microsoft.com/en-us/services/search

www.snowflake.com

vitess.io

Technical documentation

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

learn.microsoft.com/en-us/azure/search

docs.snowflake.net/manuals/index.html

vitess.io/docs

Developer

FairCom Corporation

Microsoft

Snowflake Computing Inc.

The Linux Foundation, PlanetScale

Initial release

1979

2015

2014

2013

Current release

V3, October 2020

15.0.2, December 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache Version 2.0, commercial licenses available

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++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Docker
Linux
macOS

Data scheme

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

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL 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

SQL

Support of SQL

yes

ANSI SQL queries

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

RESTful HTTP API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

C#
Java
JavaScript
Python

JavaScript (Node.js)
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++

user defined functions

yes

proprietary syntax

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

Implicit feature of the cloud service

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate 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

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.

yes

using Azure authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

Users with fine-grained authorization concept

no user groups or roles

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