DBMS > Amazon Neptune vs. BigObject vs. EsgynDB vs. Microsoft Azure AI Search

System Properties Comparison Amazon Neptune vs. BigObject vs. EsgynDB vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Analytic DBMS for real-time computations and queries

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

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Search engine

Secondary database models

Vector DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	5.75
Rank	#58	Overall
	#7	Search engines

Website

aws.amazon.com/neptune

bigobject.io

www.esgyn.cn

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

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.bigobject.io

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

Developer

Amazon

BigObject, Inc.

Esgyn

Microsoft

Initial release

2017

2015

Current release

License

Commercial or Open Source

commercial

free community edition available

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

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

hosted

Data scheme

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

none

Multi-source replication between multi datacenters

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

yes

using Azure authentication

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More resources

Recent citations in the news

How Amazon stores deliver trustworthy shopping and seller experiences using Amazon Neptune
18 September 2024, AWS Blog

Hydrating the Natural History Museum’s Planetary Knowledge Base with Amazon Neptune and Open Data on AWS
13 September 2024, AWS Blog

How Prisma Cloud built Infinity Graph using Amazon Neptune and Amazon OpenSearch Service
27 August 2024, AWS Blog

Amazon Neptune Analytics now supports openCypher queries over RDF Graphs
13 August 2024, AWS Blog

Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune
1 August 2024, AWS Blog

provided by Google News

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, Microsoft

Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard)
2 April 2024, Microsoft

From code to production: New ways Azure helps you build transformational AI experiences
21 May 2024, Microsoft

Boost your AI with Azure's new Phi model, streamlined RAG, and custom generative AI models
22 August 2024, Microsoft

Microsoft boosts Azure AI Search with more storage and support for big RAG apps
5 April 2024, VentureBeat

provided by Google News

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