DBMS > HugeGraph vs. Ingres vs. Lovefield vs. Microsoft Azure SQL Database

System Properties Comparison HugeGraph vs. Ingres vs. Lovefield vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Well established RDBMS

Embeddable relational database for web apps written in pure JavaScript

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

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	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.actian.com/databases/ingres

google.github.io/lovefield

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

Technical documentation

hugegraph.apache.org/docs

docs.actian.com/ingres

github.com/google/lovefield/blob/master/docs/spec_index.md

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

Developer

Baidu

Actian Corporation

Google

Microsoft

Initial release

2018

1974

originally developed at University Berkely in early 1970s

2014

2010

Current release

0.9

11.2, May 2022

2.1.12, February 2017

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 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

JavaScript

C++

Server operating systems

Linux
macOS
Unix

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

yes

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC

Supported programming languages

Groovy
Java
Python

JavaScript

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Transact SQL

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Ingres Replicator

none

yes, with always 3 replicas available

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

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12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

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Recent citations in the news

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
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24 September 2021, Integration Developers

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