DBMS > Alibaba Cloud Table Store vs. BaseX vs. Fauna vs. Microsoft Azure Cosmos DB vs. YottaDB

System Properties Comparison Alibaba Cloud Table Store vs. BaseX vs. Fauna vs. Microsoft Azure Cosmos DB vs. YottaDB

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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.

Globally distributed, horizontally scalable, multi-model database service

A fast and solid embedded Key-value store

Primary database model

Wide column store

Native XML DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.alibabacloud.com/product/table-store

basex.org

fauna.com

azure.microsoft.com/services/cosmos-db

yottadb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.basex.org

docs.fauna.com

learn.microsoft.com/azure/cosmos-db

yottadb.com/resources/documentation

Developer

Alibaba

BaseX GmbH

Fauna, Inc.

Microsoft

YottaDB, LLC

Initial release

2016

2007

2014

2001

Current release

10.7, August 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

hosted

Linux
OS X
Windows

hosted

Docker
Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

JSON 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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

by using the Octo plugin

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java
Python

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

Triggers

yes

via events

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

consistent hashing

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

multiple readers, single writer

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

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

User concepts

Access control

Access rights based on subaccounts and tokens

Users with fine-grained authorization concept on 4 levels

Identity management, authentication, and access control

Access rights can be defined down to the item level

Users and groups based on OS-security mechanisms

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