DBMS > atoti vs. Microsoft Azure Data Explorer vs. openGemini

System Properties Comparison atoti vs. Microsoft Azure Data Explorer vs. openGemini

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Fully managed big data interactive analytics platform

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Primary database model

Object oriented DBMS

Relational DBMS

column oriented

Time Series DBMS

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	0.43
Rank	#260	Overall
	#13	Object oriented DBMS

Score	3.12
Rank	#85	Overall
	#46	Relational DBMS

Score	0.00
Rank	#388	Overall
	#40	Time Series DBMS

Website

atoti.io

azure.microsoft.com/services/data-explorer

www.opengemini.org
github.com/openGemini

Technical documentation

docs.atoti.io

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

docs.opengemini.org/guide

Developer

ActiveViam

Microsoft

Huawei and openGemini community

Initial release

2019

2022

Current release

cloud service with continuous releases

1.1, July 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache Version 2.0

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

Server operating systems

hosted

Linux
Windows

Data scheme

Fixed schema with schema-less datatypes (dynamic)

schema-free

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

Integer, Float, Boolean, String

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

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

Kusto Query Language (KQL), SQL subset

SQL-like query language

APIs and other access methods

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

HTTP REST

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Python

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

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Azure Active Directory Authentication

Administrators and common users accounts

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More resources

Recent citations in the news

ActiveViam Announces Leadership Succession
4 September 2024, Business Wire

Overview Of Atoti: A Python BI Analytics Tool
14 May 2021, AIM

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer
31 May 2024, Microsoft

Update records in a Kusto Database (public preview)
20 February 2024, Microsoft

Microsoft is closing down another Azure-based feature in the near future
22 July 2024, Neowin

Announcing General Availability of Graph Semantics in Kusto
27 May 2024, Microsoft

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints
5 February 2024, Microsoft

provided by Google News

Open Source @ Huawei
9 February 2022, huawei.com

provided by Google News

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