DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. BaseX vs. HugeGraph vs. Oracle NoSQL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. BaseX vs. HugeGraph vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

A fast-speed and highly-scalable Graph DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Native XML DBMS

Graph DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

basex.org

github.com/hugegraph
hugegraph.apache.org

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.basex.org

hugegraph.apache.org/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

BaseX GmbH

Baidu

Oracle

Initial release

2016

2007

2018

2011

Current release

10.7, August 2023

0.9

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

Apache Version 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

hosted

Linux
OS X
Windows

Linux
macOS
Unix

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

optional

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

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

Actionscript
C
C#
Haskell
Java
JavaScript

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

Groovy
Java
Python

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

via events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

yes

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

multiple readers, single writer

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept on 4 levels

Users, roles and permissions

Access rights for users and roles

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