DBMS > Amazon Neptune vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Neptune vs. Microsoft Azure Data Explorer

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Our visitors often compare Amazon Neptune and Microsoft Azure Data Explorer with Microsoft Azure Cosmos DB, OpenSearch and Elasticsearch.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Fully managed big data interactive analytics platform

Primary database model

Graph DBMS
RDF store

Relational DBMS

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	3.00
Rank	#86	Overall
	#47	Relational DBMS

Website

aws.amazon.com/neptune

azure.microsoft.com/services/data-explorer

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.microsoft.com/en-us/azure/data-explorer

Developer

Amazon

Microsoft

Initial release

2017

2019

Current release

cloud service with continuous releases

License

Commercial or Open Source

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.

Server operating systems

hosted

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

all fields are automatically indexed

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

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.

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

with encyption-at-rest

yes

In-memory capabilities

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

User concepts

Access control

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

Azure Active Directory Authentication

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More resources

Recent citations in the news

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28 April 2025, Amazon Web Services (AWS)

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9 April 2025, Amazon Web Services (AWS)

Use Amazon Neptune Analytics to analyze relationships in your data faster, Part 1: Introducing Parquet and CSV import and export
21 January 2025, Amazon Web Services (AWS)

How Coinbase provides trustworthy financial experiences through real-time user clustering with Amazon Neptune
18 November 2024, Amazon Web Services (AWS)

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27 January 2025, Amazon Web Services (AWS)

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14 February 2025, Microsoft

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft Azure

Azure Data Explorer Supports Native Ingestion from Amazon S3
7 September 2022, infoq.com

Azure Data Explorer gets new engine, numerous enhancements and Synapse integration
14 October 2020, ZDNET

provided by Google News

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