DBMS > Alibaba Cloud Table Store vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer

System Properties Comparison Alibaba Cloud Table Store vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Fully managed big data interactive analytics platform

Primary database model

Wide column store

Document 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	0.24
Rank	#331	Overall
	#12	Wide column stores

Score	18.78
Rank	#38	Overall
	#6	Document stores

Score	6.51
Rank	#66	Overall
	#35	Relational DBMS

Website

www.alibabacloud.com/product/table-store

firebase.google.com/products/realtime-database

azure.microsoft.com/services/data-explorer

Technical documentation

www.alibabacloud.com/help/product/27278.htm

firebase.google.com/docs/database

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

Developer

Alibaba

Google

acquired by Google 2014

Microsoft

Initial release

2016

2012

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

yes

all fields are automatically indexed

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

APIs and other access methods

HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

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

Supported programming languages

Java
Python

Java
JavaScript
Objective-C

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Yes, possible languages: KQL, Python, R

Triggers

Callbacks are triggered when data changes

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

yes

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Access rights based on subaccounts and tokens

yes, based on authentication and database rules

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

Azure Data Explorer is a fast and highly scalable data exploration service for log...
» more

Competitive advantages

Kusto Query Language (innovative query language, optimized for high performance data...
» more

Typical application scenarios

IoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more

Key customers

Microsoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more

Market metrics

Azure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more

Licensing and pricing models

An Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

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12 December 2019, Paul Andlinger

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