DBMS > Alibaba Cloud Table Store vs. Couchbase vs. CouchDB vs. Faircom EDGE vs. GigaSpaces

System Properties Comparison Alibaba Cloud Table Store vs. Couchbase vs. CouchDB vs. Faircom EDGE vs. GigaSpaces

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Primary database model

Wide column store

Document store

Key-value store
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

using the Geocouch extension

Graph DBMS
Search engine

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	9.30
Rank	#45	Overall
	#7	Document stores

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Website

www.alibabacloud.com/product/table-store

www.couchbase.com

couchdb.apache.org

www.faircom.com/products/faircom-edge

www.gigaspaces.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.couchbase.com

docs.couchdb.org/en/stable

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

docs.gigaspaces.com/latest/landing.html

Developer

Alibaba

Couchbase, Inc.

Apache Software Foundation

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

FairCom Corporation

Gigaspaces Technologies

Initial release

2016

2011

2005

1979

2000

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.3.3, December 2023

V3, October 2020

15.5, September 2020

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache version 2

commercial

Restricted, free version available

Open Source

Apache Version 2; Commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

Erlang

ANSI C, C++

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Solaris
Windows

Data scheme

schema-free

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

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

XML can be used for describing objects metadata

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

ANSI SQL queries

SQL-99 for query and DML statements

APIs and other access methods

HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP/JSON API

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Supported programming languages

Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
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

.Net
C++
Java
Python
Scala

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

View functions in JavaScript

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

via the TAP protocol

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic Sharding

Sharding

improved architecture with release 2.0

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

Atomic single-row operations

ACID

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

Ephemeral buckets

yes

User concepts

Access control

Access rights based on subaccounts and tokens

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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.

Role-based access control

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