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

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

Please select another system to include it in the comparison.

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.

Scalable, ACID-compliant native distributed parallel graph platform

Fully managed big data interactive analytics platform

Primary database model

Object oriented DBMS

Graph DBMS

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	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	0.04
Rank	#375	Overall
	#40	Graph DBMS

Score	5.16
Rank	#69	Overall
	#37	Relational DBMS

Website

atoti.io

galaxybase.com

azure.microsoft.com/services/data-explorer

Technical documentation

docs.atoti.io

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

Developer

ActiveViam

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Microsoft

Initial release

2017

2019

Current release

Nov 20, November 2021

cloud service with continuous releases

License

Commercial or Open Source

commercial

free versions 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

Java

C and Java

Server operating systems

Linux

hosted

Data scheme

Strong typed schema

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

yes

all fields are automatically indexed

SQL

Support of SQL

Multidimensional Expressions (MDX)

Kusto Query Language (KQL), SQL subset

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

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

Supported programming languages

Go
Java
Python

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

Server-side scripts

Stored procedures

Python

user defined procedures and functions

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

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.

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, 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

Role-based access control

Azure Active Directory Authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

做国产图数据库，「创邻科技」将拓展国际市场| 新科技创业
5 April 2023, 36kr

创邻科技，位居IDC MarketScape中国图数据库市场领导者类别
13 September 2023, blog.csdn.net

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, azure.microsoft.com

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

General availability: New KQL function to enrich your data analysis with geographic context | Azure updates
6 June 2023, azure.microsoft.com

What is Microsoft Fabric? A big tech stack for big data
9 February 2024, InfoWorld

Azure Data Explorer and Stream Analytics for anomaly detection
16 January 2020, azure.microsoft.com

provided by Google News

Share this page