DBMS > Alibaba Cloud Table Store vs. Cassandra vs. CouchDB vs. Faircom EDGE vs. HugeGraph

System Properties Comparison Alibaba Cloud Table Store vs. Cassandra vs. CouchDB vs. Faircom EDGE vs. HugeGraph

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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

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

A fast-speed and highly-scalable Graph DBMS

Primary database model

Wide column store

Document store

Key-value store
Relational DBMS

Graph DBMS

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

using the Geocouch extension

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	9.30
Rank	#45	Overall
	#7	Document stores

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

www.alibabacloud.com/product/table-store

cassandra.apache.org

couchdb.apache.org

www.faircom.com/products/faircom-edge

github.com/hugegraph
hugegraph.apache.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

cassandra.apache.org/doc/latest

docs.couchdb.org/en/stable

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

hugegraph.apache.org/docs

Developer

Alibaba

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

FairCom Corporation

Baidu

Initial release

2016

2008

2005

1979

2018

Current release

4.1.3, July 2023

3.3.3, December 2023

V3, October 2020

0.9

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache version 2

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Erlang

ANSI C, C++

Java

Server operating systems

hosted

BSD
Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Unix

Data scheme

schema-free

Flexible Schema (defined schema, partial 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

only equality queries, not always the best performing solution

yes

via views

yes

also supports composite index and range index

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

ANSI SQL queries

APIs and other access methods

HTTP API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

RESTful HTTP/JSON API

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

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Java
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

Groovy
Java
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

.Net, JavaScript, C/C++

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Sharding

improved architecture with release 2.0

File partitioning

Customizable business rules for partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

edges in graph

Transaction concepts

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

Atomic single-row operations

Atomicity and isolation are supported for single operations

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

Access rights based on subaccounts and tokens

Access rights for users can be defined per object

Access rights for users can be defined per database

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

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

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