DBMS > HugeGraph vs. Infobright vs. Linter vs. Microsoft Azure AI Search vs. Microsoft SQL Server

System Properties Comparison HugeGraph vs. Infobright vs. Linter vs. Microsoft Azure AI Search vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

RDBMS for high security requirements

Search-as-a-service for web and mobile app development

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Spatial DBMS

Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

ignitetech.com/softwarelibrary/infobrightdb

linter.ru

azure.microsoft.com/en-us/services/search

www.microsoft.com/en-us/sql-server

Technical documentation

hugegraph.apache.org/docs

learn.microsoft.com/en-us/azure/search

learn.microsoft.com/en-US/sql/sql-server

Developer

Baidu

Ignite Technologies Inc.; formerly InfoBright Inc.

relex.ru

Microsoft

Initial release

2018

2005

1990

2015

1989

Current release

0.9

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

restricted free version is available

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

C and C++

C++

Server operating systems

Linux
macOS
Unix

Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

Linux
Windows

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.

yes

Secondary indexes

yes

also supports composite index and range index

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Groovy
Java
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C#
Java
JavaScript
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

proprietary syntax with the possibility to convert from PL/SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

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

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

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

yes

using Azure authentication

fine grained access rights according to SQL-standard

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