DBMS > AgensGraph vs. Alibaba Cloud Table Store vs. BaseX vs. Microsoft Azure Cosmos DB vs. Ultipa

System Properties Comparison AgensGraph vs. Alibaba Cloud Table Store vs. BaseX vs. Microsoft Azure Cosmos DB vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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.

Globally distributed, horizontally scalable, multi-model database service

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Graph DBMS
Relational DBMS

Wide column store

Native XML DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

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

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

bitnine.net/agensgraph

www.alibabacloud.com/product/table-store

basex.org

azure.microsoft.com/services/cosmos-db

www.ultipa.com

Technical documentation

bitnine.net/documentation

www.alibabacloud.com/help/en/tablestore

docs.basex.org

learn.microsoft.com/azure/cosmos-db

www.ultipa.com/document

Developer

Bitnine Global Inc.

Alibaba

BaseX GmbH

Microsoft

Ultipa

Initial release

2016

2007

2014

2019

Current release

2.1, December 2018

11.0, June 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

BSD license

commercial

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

hosted

Data scheme

depending on used data model

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

yes

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

Java
Python

Actionscript
C
C#
Haskell
Java
JavaScript

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

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

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

via events

JavaScript

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

none

yes

Implicit feature of the cloud service

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

ACID

Atomic single-row operations

multiple readers, single writer

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights based on subaccounts and tokens

Users with fine-grained authorization concept on 4 levels

Access rights can be defined down to the item level

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