DBMS > Alibaba Cloud Table Store vs. Faircom EDGE vs. FatDB vs. JanusGraph vs. Sadas Engine

System Properties Comparison Alibaba Cloud Table Store vs. Faircom EDGE vs. FatDB vs. JanusGraph vs. Sadas Engine

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

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

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 Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Wide column store

Key-value store
Relational DBMS

Document store
Key-value store

Graph DBMS

Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.faircom.com/products/faircom-edge

janusgraph.org

www.sadasengine.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

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

docs.janusgraph.org

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Alibaba

FairCom Corporation

FatCloud

Linux Foundation; originally developed as Titan by Aurelius

SADAS s.r.l.

Initial release

2016

1979

2012

2017

2006

Current release

V3, October 2020

0.6.3, February 2023

8.0

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

commercial

free trial 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++

Java

C++

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Windows

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

schema-free

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

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

yes

SQL

Support of SQL

yes

ANSI SQL queries

Via inetgration in SQL Server

yes

APIs and other access methods

HTTP API

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java
Python

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

Clojure
Java
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

File partitioning

Customizable business rules for partitioning

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights based on subaccounts and tokens

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

Can implement custom security layer via applications

User authentification and security via Rexster Graph Server

Access rights for users, groups and roles according to SQL-standard

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