DBMS > Alibaba Cloud Table Store vs. Amazon Redshift vs. Badger vs. Faircom DB vs. Faircom EDGE

System Properties Comparison Alibaba Cloud Table Store vs. Amazon Redshift vs. Badger vs. Faircom DB vs. Faircom EDGE

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Large scale data warehouse service for use with business intelligence tools

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Primary database model

Wide column store

Relational DBMS

Key-value store

Key-value store
Relational DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

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

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/redshift

github.com/dgraph-io/badger

www.faircom.com/products/faircom-db

www.faircom.com/products/faircom-edge

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/redshift

godoc.org/github.com/dgraph-io/badger

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

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

Developer

Alibaba

Amazon (based on PostgreSQL)

DGraph Labs

FairCom Corporation

Initial release

2016

2012

2017

1979

Current release

V12, November 2020

V3, October 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Restricted, free version available

commercial

Restricted, free version 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

hosted

BSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Android
Linux

ARM, x86
Raspbian
Windows

Data scheme

schema-free

yes

schema-free

schema free, schema optional, schema required, partial schema,

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

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, ANSI SQL with proprietary extensions

yes

ANSI SQL queries

APIs and other access methods

HTTP API

JDBC
ODBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

File partitioning

Customizable business rules for partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Synchronous and asynchronous realtime replication based on transaction logs

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency
Tunable 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

Atomic single-row operations

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Fine grained access rights according to SQL-standard with additional protections for files

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

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.