DBMS > EsgynDB vs. Infobright vs. JanusGraph vs. Microsoft Azure AI Search

System Properties Comparison EsgynDB vs. Infobright vs. JanusGraph vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Relational DBMS

Graph DBMS

Search engine

Secondary database models

Vector DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	5.75
Rank	#58	Overall
	#7	Search engines

Website

www.esgyn.cn

ignitetech.com/softwarelibrary/infobrightdb

janusgraph.org

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

Technical documentation

docs.janusgraph.org

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

Developer

Esgyn

Ignite Technologies Inc.; formerly InfoBright Inc.

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2015

2005

2017

2015

Current release

1.0.0, October 2023

License

Commercial or Open Source

commercial

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

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

C++, Java

Java

Server operating systems

Linux

Linux
Windows

Linux
OS X
Unix
Windows

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.

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

Clojure
Java
Python

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

User authentification and security via Rexster Graph Server

yes

using Azure authentication

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