DBMS > Alibaba Cloud Table Store vs. Amazon Redshift vs. Fauna vs. MarkLogic

System Properties Comparison Alibaba Cloud Table Store vs. Amazon Redshift vs. Fauna vs. MarkLogic

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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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Operational and transactional Enterprise NoSQL database

Primary database model

Wide column store

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/redshift

fauna.com

www.progress.com/marklogic

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/redshift

docs.fauna.com

www.progress.com/marklogic/documentation

Developer

Alibaba

Amazon (based on PostgreSQL)

Fauna, Inc.

MarkLogic Corp.

Initial release

2016

2012

2014

2001

Current release

11.0, December 2022

License

Commercial or Open Source

commercial

restricted free version is 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

Scala

C++

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL92

APIs and other access methods

HTTP API

JDBC
ODBC

RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

Atomic single-row operations

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

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

yes, with Range Indexes

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Identity management, authentication, and access control

Role-based access control at the document and subdocument levels

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