DBMS > HugeGraph vs. Microsoft Azure SQL Database vs. Oracle Rdb vs. Snowflake

System Properties Comparison HugeGraph vs. Microsoft Azure SQL Database vs. Oracle Rdb vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

www.oracle.com/database/technologies/related/rdb.html

www.snowflake.com

Technical documentation

hugegraph.apache.org/docs

docs.microsoft.com/en-us/azure/azure-sql

www.oracle.com/database/technologies/related/rdb-doc.html

docs.snowflake.net/manuals/index.html

Developer

Baidu

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Snowflake Computing Inc.

Initial release

2018

2010

1984

2014

Current release

0.9

V12

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
macOS
Unix

hosted

HP Open VMS

hosted

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Groovy
Java
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Transact SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

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

Users, roles and permissions

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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