DBMS > Amazon Redshift vs. Faircom EDGE vs. OpenMLDB vs. SwayDB vs. Teradata

System Properties Comparison Amazon Redshift vs. Faircom EDGE vs. OpenMLDB vs. SwayDB vs. Teradata

Editorial information provided by DB-Engines

Name

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

An open-source machine learning database that provides a feature platform for training and inference

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

aws.amazon.com/redshift

www.faircom.com/products/faircom-edge

openmldb.ai

swaydb.simer.au

www.teradata.com

Technical documentation

docs.aws.amazon.com/redshift

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

openmldb.ai/docs/zh/main

docs.teradata.com

Developer

Amazon (based on PostgreSQL)

FairCom Corporation

4 Paradigm Inc.

Simer Plaha

Teradata

Initial release

2012

1979

2020

2018

1984

Current release

V3, October 2020

2024-2 February 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

GNU Affero GPL V3.0

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++, Java, Scala

Scala

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Linux

hosted
Linux

Data scheme

yes

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

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

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

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL queries

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC

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

JDBC
SQLAlchemy

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

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

C++
Go
Java
Python
Scala

Java
Kotlin
Scala

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

horizontal partitioning

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

none

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

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

when using SQL

yes

Transaction concepts

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

ACID

Atomic execution of operations

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.

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.