DBMS > Amazon Redshift vs. Faircom EDGE vs. FatDB vs. Qdrant vs. SWC-DB

System Properties Comparison Amazon Redshift vs. Faircom EDGE vs. FatDB vs. Qdrant vs. SWC-DB

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.

Description

Large scale data warehouse service for use with business intelligence tools

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

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

A high-performance vector database with neural network or semantic-based matching

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store
Key-value store

Vector DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

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

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

aws.amazon.com/redshift

www.faircom.com/products/faircom-edge

github.com/qdrant/qdrant
qdrant.tech

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.aws.amazon.com/redshift

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

qdrant.tech/documentation

Developer

Amazon (based on PostgreSQL)

FairCom Corporation

FatCloud

Qdrant

Alex Kashirin

Initial release

2012

1979

2012

2021

2020

Current release

V3, October 2020

0.5, April 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3

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++

Rust

C++

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Windows

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

Numbers, Strings, Geo, Boolean

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

restricted

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL queries

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

when using SQL

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

Can implement custom security layer via applications

Key-based authentication

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