SlideShare a Scribd company logo
Azure Data Overview
…dove metto i miei dati?...
Agenda
Azure SQL
Database
Azure
DocumentDB
Azure Table
Storage
Azure Redis Cache Azure Search
…almeno fino a ieri
Agenda (post //build/)
Azure SQL
Database
Azure CosmosDB
(DocumentDB, MongoDB, Graph, Key-value)
Azure Table
Storage
Azure Redis Cache Azure Search
Azure Database
for MySQL
Azure Database
for PostgreSQL
Azure SQL Database
SQL Server (everywhere)
Azure SQL Database
Azure SQL Database is a relational database-as-a-service (DBaaS)
hosted in the Azure cloud that falls into the industry categories
of Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS).
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-paas-vs-sql-server-iaas
Azure SQL Database
Azure SQL Database is optimized to reduce overall costs to the
minimum for provisioning and managing many databases. It reduces
ongoing administration costs because you do not have to manage any
virtual machines, operating system or database software.
Azure SQL Database
Azure SQL Database is optimized to reduce overall costs to the
minimum for provisioning and managing many databases. It reduces
ongoing administration costs because you do not have to manage any
virtual machines, operating system or database software.
You do not have to manage:
Azure SQL Database
Azure SQL Database is optimized to reduce overall costs to the
minimum for provisioning and managing many databases. It reduces
ongoing administration costs because you do not have to manage any
virtual machines, operating system or database software.
You do not have to manage:
upgrades
Azure SQL Database
Azure SQL Database is optimized to reduce overall costs to the
minimum for provisioning and managing many databases. It reduces
ongoing administration costs because you do not have to manage any
virtual machines, operating system or database software.
You do not have to manage:
high availability
Azure SQL Database
Azure SQL Database is optimized to reduce overall costs to the
minimum for provisioning and managing many databases. It reduces
ongoing administration costs because you do not have to manage any
virtual machines, operating system or database software.
You do not have to manage:
backups
Service tiers
• Basic: Best suited for a small database, supporting typically one single active operation at a
given time. Examples include databases used for development or testing, or small-scale
infrequently used applications.
• Standard: The go-to option for cloud applications with low to medium IO performance
requirements, supporting multiple concurrent queries. Examples include workgroup or web
applications.
• Premium: Designed for high transactional volume with high IO performance requirements,
supporting many concurrent users. Examples are databases supporting mission critical
applications.
• Premium RS: Designed for IO-intensive workloads that do not require the highest availability
guarantees. Examples include testing high-performance workloads, or an analytical workload
where the database is not the system of record.
Service tiers
• After initially picking a service tier and performance level, you can
scale a single database up or down dynamically
• Changing the service tier and/or performance level of a database
creates a replica of the original database at the new performance
level, and then switches connections over to the replica.
• No data is lost during this process but during the brief moment when
we switch over to the replica, connections to the database are
disabled, so some transactions in flight may be rolled back.
Create Azure Sql Database
• Azure Portal
• Azure CLI
• Powershell
Demo
Elastic pools
• SQL Database elastic pools are a simple, cost-effective solution for
managing and scaling multiple databases that have varying and
unpredictable usage demands
• Within the pool, individual databases are given the flexibility to auto-
scale within set parameters. Under heavy load, a database can
consume more eDTUs to meet demand. Databases under light loads
consume less, and databases under no load consume no eDTUs.
Elastic pool
Elastic pool
Elastic pool
Elastic pool
Elastic pool
Demo
Business continuity
• Backup
• Active Geo-Replication
Business continuity: backup
• SQL Database automatically performs a combination of full database
backups weekly, differential database backups hourly, and transaction
log backups every five minutes to protect your business from data
loss. These backups are stored in geo-redundant storage
• Use automated backups as your business continuity and recovery
mechanism if your application:
• Is not considered mission critical
• Has a low rate of data change (low transactions per hour) and losing up to an
hour of change is an acceptable data loss
• Is cost sensitive
Business continuity: active geo-replication
• Is possible to use Active Geo-Replication to configure a database to
have up to four readable secondary databases in the regions of your
choice
• These secondary databases are kept synchronized with the primary
database using an asynchronous replication mechanism
• Active Geo-Replication can also be used to provide better query
performance for read-only queries to geographically dispersed users.
Demo
Monitoring
• Metrics
• SQL Database advisor
• Query Performance Insight
Demo
Azure Database Migration Service
• Using database migration service simplifies the migration of existing
on-premises SQL Server, Oracle, and MySQL databases to Azure,
whether your target database is Azure SQL Database, Azure SQL
Database Managed Instance or Microsoft SQL Server in an Azure
virtual machine.
Azure Database Migration Service
• Using database migration service simplifies the migration of existing
on-premises SQL Server, Oracle, and MySQL databases to Azure,
whether your target database is Azure SQL Database, Azure SQL
Database Managed Instance or Microsoft SQL Server in an Azure
virtual machine.
PostgreSQL / MySQL
Azure database for PostgreSQL/MySQL
• Azure Database for PostgreSQL/MySQL is a relational database service
in the Microsoft cloud built for developers based on the community
version of open source PostgreSQL and MySQL Community
Edition database engine. It provides:
• Predictable performance at multiple service levels
• Dynamic scalability with no application downtime
• Built-in high availability
• Data protection
Demo
Azure Table Storage
Azure Table Storage
Azure Table storage is a service that stores structured NoSQL data in
the cloud, providing a key/attribute store with a schemaless design
https://docs.microsoft.com/en-us/azure/storage/storage-dotnet-how-to-use-tables
Table service concepts
• Storage Account
• Table: a table is a collection of entities
• Entitiy: An entity is a set of properties (similar
to a database row). An entity can be up to 1MB
in size
• Properties: A property is a name-value pair.
Each entity can include up to 252 properties to
store data
Table entities
• Table entities represent the units of data stored in a table and are
similar to rows in a typical relational database table
• Each entity defines a collection of properties
• Entities must define the following three system properties as part of
the property collection:
• PartitionKey
• RowKey
• Timestamp
Table partitions
Queries performance
Azure Storage: paper
http://sigops.org/sosp/sosp11/current/2011-Cascais/printable/11-calder.pdf
Azure CosmosDB
Azure CosmosDB
Azure Cosmos DB is Microsoft's globally distributed,
multi-model database
https://docs.microsoft.com/en-us/azure/cosmos-db/introduction
Azure CosmosDB
Global distribution
• Within a given region, all resources
are horizontally partitioned using
resource partitions (local
distribution).
• Each resource partition is also
replicated across geographical regions
(global distribution).
Multi-model, multi API-support
• The core content-model of Cosmos DB’s
database engine is based on atom-
record-sequence (ARS)
• Atoms consist of a small set of primitive
types like string, bool, and number. Records
are structs composed of these types.
Sequences are arrays consisting of atoms,
records, or sequences.
• The database engine can efficiently
translate and project different data
models onto the ARS-based data model.
Multiple consistency models
• It’s possible to configure the default consistency level on Cosmos DB
account, and later override the consistency on a specific read request
Guaranteed SLA
• Availability: 99.99% uptime availability SLA for each of the data and control plane
operations.
• Throughput: 99.99% of requests complete successfully
• Latency: 99.99% of <10 ms latencies at the 99th percentile
• Consistency: 100% of read requests will meet the consistency guarantee for the consistency
level requested by you.
Demo
CosmosDB: indexing
• CosmosDB indexes, by default, each document’s attribute
• Automatic indexing of documents without requiring schema or
secondary indexes is a key capability of CosmosDB and is enabled by
write-optimized, lock-free and log-structured index maintenance
techniques
CosmosDB: indexing policy
• The indexing policy of each collection allows you to make
performance and storage trade-offs associated with indexing
• Choose whether the collection automatically indexes all of the documents or
not
• Choose whether to include or exclude specific paths or patterns in your
documents from the index
• Choose between synchronous (consistent) and asynchronous (lazy) index
updates
• The indexing policy can be changed
Demo
Azure Redis Cache
Azure Redis Cache
• Redis is an advanced key-value store, where keys can contain data
structures such as strings, hashes, lists, sets, and sorted sets. Redis
supports a set of atomic operations on these data types.
• Azure Redis Cache uses Redis authentication and also supports SSL
connections to Redis.
Service tiers
• Basic: Single node, multiple sizes, ideal for development/test and non-critical workloads. The
Basic tier has no SLA.
• Standard: A replicated cache in a two-node primary/secondary configuration managed by
Microsoft, with a high-availability SLA.
• Premium: All of the Standard tier features, plus:
• Redis data persistence: allows you to persist the cache data in an Azure Storage account
• Redis cluster
• Enhanced security and isolation
• Reboot
• Schedule updates
Demo
Azure Search
Azure Search
Azure Search is a cloud search-as-a-service solution that delegates
server and infrastructure management to Microsoft, leaving you with a
ready-to-use service that you can populate with your data and then use
to add search to your web or mobile application.
https://docs.microsoft.com/en-us/azure/search/search-what-is-azure-search
Azure Search
• Full text search and text analysis
• Search suggestions
• Facet queries
• Scoring
• …
• Language support
• Data integration
Service tiers
• Free: A shared service, at no charge, used for evaluation, investigation, or small workloads.
• Basic: Small production workloads on dedicated hardware. Highly available.
• Standard:
• S1
• S2
• S3
• S3 HD
Indexers
• An indexer in Azure Search is a crawler that extracts searchable data
and metadata from an external data source and populates an index
based on field-to-field mappings between the index and your data
source.
• You can use an indexer as the sole means for data ingestion, or use a
combination of techniques
• You can run indexers on demand or on a recurring data refresh
schedule
Indexer types
• Azure Blob Storage indexer
• Azure Table Storage indexer
• Azure SQL indexer
• Azure CosmosDB indexer
Demo
Wrap-up
SQL IaaS vs SQL Database
• Existing applications that
require fast migration to the
cloud with minimal changes.
• SQL Server instances with up to
64 TB of storage. The instance
can support as many databases
as needed.
• Migrating and building
enterprise and hybrid
applications.
• New cloud-designed
applications that have time
constraints in development and
marketing.
• Databases of up to 1 TB, or
larger databases that can
be horizontally or vertically
partitioned using a scale-out
pattern.
• Building Software-as-a-Service
(SaaS) applications.
SQL IaaS vs SQL Database: features
• https://docs.microsoft.com/en-us/azure/sql-database/sql-database-
features
Extra-time
Transient fault handling
Transient faults can occur in any environment, on any platform or
operating system, and in any kind of application
Transient fault handling: cloud
• Many resources in a cloud environment are shared, and access to
these resources is subject to throttling in order to protect the
resource
• Cloud environments are built using vast numbers of commodity
hardware units
• There are often more hardware components, including network
infrastructure such as routers and load balancers, between the
application and the resources and services it uses
• Network conditions between the client and the server may be
variable
Transient fault handling: challanges
• The application must be able to detect faults when they occur, and
determine if these faults are likely to be transient, more long-lasting,
or are terminal failures
• The application must be able to retry the operation if it determines
that the fault is likely to be transient
• The application must use an appropriate strategy for the retries:
• Exponential back-off
• Incremental intervals
• Regular intervals
• Immediate retry
• Randomization
About me
Alessandro Melchiori
@amelchiori
http://melkio.codiceplastico.com
Azure data platform overview

More Related Content

What's hot

Azure - Data Platform
Azure - Data PlatformAzure - Data Platform
Azure - Data Platform
giventocode
 
The Evolution of SQL Server as a Service - SQL Azure Managed Instance
The Evolution of SQL Server as a Service - SQL Azure Managed InstanceThe Evolution of SQL Server as a Service - SQL Azure Managed Instance
The Evolution of SQL Server as a Service - SQL Azure Managed Instance
Javier Villegas
 
Azure data platform overview
Azure data platform overviewAzure data platform overview
Azure data platform overview
James Serra
 
Migrating on premises workload to azure sql database
Migrating on premises workload to azure sql databaseMigrating on premises workload to azure sql database
Migrating on premises workload to azure sql database
PARIKSHIT SAVJANI
 
Implement SQL Server on an Azure VM
Implement SQL Server on an Azure VMImplement SQL Server on an Azure VM
Implement SQL Server on an Azure VM
James Serra
 
Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020
Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020
Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020
Timothy McAliley
 
Introducing Azure SQL Data Warehouse
Introducing Azure SQL Data WarehouseIntroducing Azure SQL Data Warehouse
Introducing Azure SQL Data Warehouse
James Serra
 
Introduction to Azure SQL DB
Introduction to Azure SQL DBIntroduction to Azure SQL DB
Introduction to Azure SQL DB
Christopher Foot
 
HA/DR options with SQL Server in Azure and hybrid
HA/DR options with SQL Server in Azure and hybridHA/DR options with SQL Server in Azure and hybrid
HA/DR options with SQL Server in Azure and hybrid
James Serra
 
Azure Cosmos DB
Azure Cosmos DBAzure Cosmos DB
Azure Cosmos DB
Mohamed Tawfik
 
Benefits of the Azure cloud
Benefits of the Azure cloudBenefits of the Azure cloud
Benefits of the Azure cloud
James Serra
 
Azure SQL Database Managed Instance - technical overview
Azure SQL Database Managed Instance - technical overviewAzure SQL Database Managed Instance - technical overview
Azure SQL Database Managed Instance - technical overview
George Walters
 
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...
Sandy Winarko
 
Microsoft certified azure developer associate
Microsoft certified azure developer associateMicrosoft certified azure developer associate
Microsoft certified azure developer associate
Gaurav Singh
 
A Tour of Azure SQL Databases (NOVA SQL UG 2020)
A Tour of Azure SQL Databases  (NOVA SQL UG 2020)A Tour of Azure SQL Databases  (NOVA SQL UG 2020)
A Tour of Azure SQL Databases (NOVA SQL UG 2020)
Timothy McAliley
 
Data saturday Oslo Azure Purview Erwin de Kreuk
Data saturday Oslo Azure Purview Erwin de KreukData saturday Oslo Azure Purview Erwin de Kreuk
Data saturday Oslo Azure Purview Erwin de Kreuk
Erwin de Kreuk
 
Modern Data Warehouse Overview
Modern Data Warehouse OverviewModern Data Warehouse Overview
Modern Data Warehouse Overview
John Chang
 
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp
 
What’s new in SQL Server 2017
What’s new in SQL Server 2017What’s new in SQL Server 2017
What’s new in SQL Server 2017
James Serra
 
Azure SQL Managed Instance - SqlBits 2019
Azure SQL Managed Instance - SqlBits 2019Azure SQL Managed Instance - SqlBits 2019
Azure SQL Managed Instance - SqlBits 2019
Jovan Popovic
 

What's hot (20)

Azure - Data Platform
Azure - Data PlatformAzure - Data Platform
Azure - Data Platform
 
The Evolution of SQL Server as a Service - SQL Azure Managed Instance
The Evolution of SQL Server as a Service - SQL Azure Managed InstanceThe Evolution of SQL Server as a Service - SQL Azure Managed Instance
The Evolution of SQL Server as a Service - SQL Azure Managed Instance
 
Azure data platform overview
Azure data platform overviewAzure data platform overview
Azure data platform overview
 
Migrating on premises workload to azure sql database
Migrating on premises workload to azure sql databaseMigrating on premises workload to azure sql database
Migrating on premises workload to azure sql database
 
Implement SQL Server on an Azure VM
Implement SQL Server on an Azure VMImplement SQL Server on an Azure VM
Implement SQL Server on an Azure VM
 
Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020
Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020
Data Migration to Azure SQL and Azure SQL Managed Instance - June 19 2020
 
Introducing Azure SQL Data Warehouse
Introducing Azure SQL Data WarehouseIntroducing Azure SQL Data Warehouse
Introducing Azure SQL Data Warehouse
 
Introduction to Azure SQL DB
Introduction to Azure SQL DBIntroduction to Azure SQL DB
Introduction to Azure SQL DB
 
HA/DR options with SQL Server in Azure and hybrid
HA/DR options with SQL Server in Azure and hybridHA/DR options with SQL Server in Azure and hybrid
HA/DR options with SQL Server in Azure and hybrid
 
Azure Cosmos DB
Azure Cosmos DBAzure Cosmos DB
Azure Cosmos DB
 
Benefits of the Azure cloud
Benefits of the Azure cloudBenefits of the Azure cloud
Benefits of the Azure cloud
 
Azure SQL Database Managed Instance - technical overview
Azure SQL Database Managed Instance - technical overviewAzure SQL Database Managed Instance - technical overview
Azure SQL Database Managed Instance - technical overview
 
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...
PaaSport to Paradise: Lifting & Shifting with Azure SQL Database/Managed Inst...
 
Microsoft certified azure developer associate
Microsoft certified azure developer associateMicrosoft certified azure developer associate
Microsoft certified azure developer associate
 
A Tour of Azure SQL Databases (NOVA SQL UG 2020)
A Tour of Azure SQL Databases  (NOVA SQL UG 2020)A Tour of Azure SQL Databases  (NOVA SQL UG 2020)
A Tour of Azure SQL Databases (NOVA SQL UG 2020)
 
Data saturday Oslo Azure Purview Erwin de Kreuk
Data saturday Oslo Azure Purview Erwin de KreukData saturday Oslo Azure Purview Erwin de Kreuk
Data saturday Oslo Azure Purview Erwin de Kreuk
 
Modern Data Warehouse Overview
Modern Data Warehouse OverviewModern Data Warehouse Overview
Modern Data Warehouse Overview
 
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
 
What’s new in SQL Server 2017
What’s new in SQL Server 2017What’s new in SQL Server 2017
What’s new in SQL Server 2017
 
Azure SQL Managed Instance - SqlBits 2019
Azure SQL Managed Instance - SqlBits 2019Azure SQL Managed Instance - SqlBits 2019
Azure SQL Managed Instance - SqlBits 2019
 

Similar to Azure data platform overview

Scalable relational database with SQL Azure
Scalable relational database with SQL AzureScalable relational database with SQL Azure
Scalable relational database with SQL Azure
Shy Engelberg
 
Tech-Spark: Azure SQL Databases
Tech-Spark: Azure SQL DatabasesTech-Spark: Azure SQL Databases
Tech-Spark: Azure SQL Databases
Ralph Attard
 
Azure SQL Database
Azure SQL Database Azure SQL Database
Azure SQL Database
nj-azure
 
DBAM-01.pdf
DBAM-01.pdfDBAM-01.pdf
DBAM-01.pdf
hania80
 
Database Administration & Management - 01
Database Administration & Management - 01Database Administration & Management - 01
Database Administration & Management - 01
FaisalMashood
 
AWS Certified Cloud Practitioner Course S11-S17
AWS Certified Cloud Practitioner Course S11-S17AWS Certified Cloud Practitioner Course S11-S17
AWS Certified Cloud Practitioner Course S11-S17
Neal Davis
 
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018 Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018
Antonios Chatzipavlis
 
Clash of Technologies Google Cloud vs Microsoft Azure
Clash of Technologies Google Cloud vs Microsoft AzureClash of Technologies Google Cloud vs Microsoft Azure
Clash of Technologies Google Cloud vs Microsoft Azure
Mihail Mateev
 
Azure SQL Database
Azure SQL DatabaseAzure SQL Database
Azure SQL Database
Palash Debnath
 
Azure from scratch part 3 By Girish Kalamati
Azure from scratch part 3 By Girish KalamatiAzure from scratch part 3 By Girish Kalamati
Azure from scratch part 3 By Girish Kalamati
Girish Kalamati
 
Cloud architectural patterns and Microsoft Azure tools
Cloud architectural patterns and Microsoft Azure toolsCloud architectural patterns and Microsoft Azure tools
Cloud architectural patterns and Microsoft Azure tools
Pushkar Chivate
 
Bases de datos en la nube con AWS
Bases de datos en la nube con AWSBases de datos en la nube con AWS
Bases de datos en la nube con AWS
Amazon Web Services LATAM
 
amazon database
amazon databaseamazon database
amazon database
PrasannaBhalerao3
 
autonomous-database-100.pdf
autonomous-database-100.pdfautonomous-database-100.pdf
autonomous-database-100.pdf
TrLuNguyn
 
01_DP-300T00A-Intro.pptx
01_DP-300T00A-Intro.pptx01_DP-300T00A-Intro.pptx
01_DP-300T00A-Intro.pptx
KareemBullard1
 
AWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDS
AWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDSAWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDS
AWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDS
Amazon Web Services
 
Amazon Web Services - Relational Database Service Meetup
Amazon Web Services - Relational Database Service MeetupAmazon Web Services - Relational Database Service Meetup
Amazon Web Services - Relational Database Service Meetup
cyrilkhairallah
 
Afternoons with Azure - Azure Data Services
Afternoons with Azure - Azure Data ServicesAfternoons with Azure - Azure Data Services
Afternoons with Azure - Azure Data Services
CCG
 
OSS DB on Azure
OSS DB on AzureOSS DB on Azure
OSS DB on Azure
rockplace
 

Similar to Azure data platform overview (20)

Scalable relational database with SQL Azure
Scalable relational database with SQL AzureScalable relational database with SQL Azure
Scalable relational database with SQL Azure
 
AZURE Data Related Services
AZURE Data Related ServicesAZURE Data Related Services
AZURE Data Related Services
 
Tech-Spark: Azure SQL Databases
Tech-Spark: Azure SQL DatabasesTech-Spark: Azure SQL Databases
Tech-Spark: Azure SQL Databases
 
Azure SQL Database
Azure SQL Database Azure SQL Database
Azure SQL Database
 
DBAM-01.pdf
DBAM-01.pdfDBAM-01.pdf
DBAM-01.pdf
 
Database Administration & Management - 01
Database Administration & Management - 01Database Administration & Management - 01
Database Administration & Management - 01
 
AWS Certified Cloud Practitioner Course S11-S17
AWS Certified Cloud Practitioner Course S11-S17AWS Certified Cloud Practitioner Course S11-S17
AWS Certified Cloud Practitioner Course S11-S17
 
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018 Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018
 
Clash of Technologies Google Cloud vs Microsoft Azure
Clash of Technologies Google Cloud vs Microsoft AzureClash of Technologies Google Cloud vs Microsoft Azure
Clash of Technologies Google Cloud vs Microsoft Azure
 
Azure SQL Database
Azure SQL DatabaseAzure SQL Database
Azure SQL Database
 
Azure from scratch part 3 By Girish Kalamati
Azure from scratch part 3 By Girish KalamatiAzure from scratch part 3 By Girish Kalamati
Azure from scratch part 3 By Girish Kalamati
 
Cloud architectural patterns and Microsoft Azure tools
Cloud architectural patterns and Microsoft Azure toolsCloud architectural patterns and Microsoft Azure tools
Cloud architectural patterns and Microsoft Azure tools
 
Bases de datos en la nube con AWS
Bases de datos en la nube con AWSBases de datos en la nube con AWS
Bases de datos en la nube con AWS
 
amazon database
amazon databaseamazon database
amazon database
 
autonomous-database-100.pdf
autonomous-database-100.pdfautonomous-database-100.pdf
autonomous-database-100.pdf
 
01_DP-300T00A-Intro.pptx
01_DP-300T00A-Intro.pptx01_DP-300T00A-Intro.pptx
01_DP-300T00A-Intro.pptx
 
AWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDS
AWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDSAWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDS
AWSome Day 2016 - Module 4: Databases: Amazon DynamoDB and Amazon RDS
 
Amazon Web Services - Relational Database Service Meetup
Amazon Web Services - Relational Database Service MeetupAmazon Web Services - Relational Database Service Meetup
Amazon Web Services - Relational Database Service Meetup
 
Afternoons with Azure - Azure Data Services
Afternoons with Azure - Azure Data ServicesAfternoons with Azure - Azure Data Services
Afternoons with Azure - Azure Data Services
 
OSS DB on Azure
OSS DB on AzureOSS DB on Azure
OSS DB on Azure
 

More from Alessandro Melchiori

Scale your (aks) cluster, luke!
Scale your (aks) cluster, luke!Scale your (aks) cluster, luke!
Scale your (aks) cluster, luke!
Alessandro Melchiori
 
A quick introduction to AKS
A quick introduction to AKSA quick introduction to AKS
A quick introduction to AKS
Alessandro Melchiori
 
Developing reliable applications with .net core and AKS
Developing reliable applications with .net core and AKSDeveloping reliable applications with .net core and AKS
Developing reliable applications with .net core and AKS
Alessandro Melchiori
 
VS Code tools for docker
VS Code tools for dockerVS Code tools for docker
VS Code tools for docker
Alessandro Melchiori
 
Developing reliable applications with .net core and AKS
Developing reliable applications with .net core and AKSDeveloping reliable applications with .net core and AKS
Developing reliable applications with .net core and AKS
Alessandro Melchiori
 
How to search...better! (azure search)
How to search...better! (azure search)How to search...better! (azure search)
How to search...better! (azure search)
Alessandro Melchiori
 
AKS: k8s e azure
AKS: k8s e azureAKS: k8s e azure
AKS: k8s e azure
Alessandro Melchiori
 
How to search...better!
How to search...better!How to search...better!
How to search...better!
Alessandro Melchiori
 
A quick tour around Azure Dev Spaces
A quick tour around Azure Dev SpacesA quick tour around Azure Dev Spaces
A quick tour around Azure Dev Spaces
Alessandro Melchiori
 
Azure functions: from a function to a whole application in 60 minutes
Azure functions: from a function to a whole application in 60 minutesAzure functions: from a function to a whole application in 60 minutes
Azure functions: from a function to a whole application in 60 minutes
Alessandro Melchiori
 
Aks: k8s e azure
Aks:  k8s e azureAks:  k8s e azure
Aks: k8s e azure
Alessandro Melchiori
 
Monitoring docker: from zero to Azure
Monitoring docker: from zero to AzureMonitoring docker: from zero to Azure
Monitoring docker: from zero to Azure
Alessandro Melchiori
 
Cooking Akka.net and Azure Service Fabric together
Cooking Akka.net and Azure Service Fabric togetherCooking Akka.net and Azure Service Fabric together
Cooking Akka.net and Azure Service Fabric together
Alessandro Melchiori
 
ACR + ACS + VSTS: a complete ALM pipeline with docker and azure
ACR + ACS + VSTS: a complete ALM pipeline with docker and azureACR + ACS + VSTS: a complete ALM pipeline with docker and azure
ACR + ACS + VSTS: a complete ALM pipeline with docker and azure
Alessandro Melchiori
 
Docker & Azure
Docker & AzureDocker & Azure
Docker & Azure
Alessandro Melchiori
 
Docker and Azure
Docker and AzureDocker and Azure
Docker and Azure
Alessandro Melchiori
 
Come ti "pusho" il web con WebSockets: da 0 a SignalR
Come ti "pusho" il web con WebSockets: da 0 a SignalR Come ti "pusho" il web con WebSockets: da 0 a SignalR
Come ti "pusho" il web con WebSockets: da 0 a SignalR
Alessandro Melchiori
 
Docker &amp; azure
Docker &amp; azureDocker &amp; azure
Docker &amp; azure
Alessandro Melchiori
 
Azure service fabric: a gentle introduction
Azure service fabric: a gentle introductionAzure service fabric: a gentle introduction
Azure service fabric: a gentle introduction
Alessandro Melchiori
 
From CRUD to messages: a true story
From CRUD to messages: a true storyFrom CRUD to messages: a true story
From CRUD to messages: a true story
Alessandro Melchiori
 

More from Alessandro Melchiori (20)

Scale your (aks) cluster, luke!
Scale your (aks) cluster, luke!Scale your (aks) cluster, luke!
Scale your (aks) cluster, luke!
 
A quick introduction to AKS
A quick introduction to AKSA quick introduction to AKS
A quick introduction to AKS
 
Developing reliable applications with .net core and AKS
Developing reliable applications with .net core and AKSDeveloping reliable applications with .net core and AKS
Developing reliable applications with .net core and AKS
 
VS Code tools for docker
VS Code tools for dockerVS Code tools for docker
VS Code tools for docker
 
Developing reliable applications with .net core and AKS
Developing reliable applications with .net core and AKSDeveloping reliable applications with .net core and AKS
Developing reliable applications with .net core and AKS
 
How to search...better! (azure search)
How to search...better! (azure search)How to search...better! (azure search)
How to search...better! (azure search)
 
AKS: k8s e azure
AKS: k8s e azureAKS: k8s e azure
AKS: k8s e azure
 
How to search...better!
How to search...better!How to search...better!
How to search...better!
 
A quick tour around Azure Dev Spaces
A quick tour around Azure Dev SpacesA quick tour around Azure Dev Spaces
A quick tour around Azure Dev Spaces
 
Azure functions: from a function to a whole application in 60 minutes
Azure functions: from a function to a whole application in 60 minutesAzure functions: from a function to a whole application in 60 minutes
Azure functions: from a function to a whole application in 60 minutes
 
Aks: k8s e azure
Aks:  k8s e azureAks:  k8s e azure
Aks: k8s e azure
 
Monitoring docker: from zero to Azure
Monitoring docker: from zero to AzureMonitoring docker: from zero to Azure
Monitoring docker: from zero to Azure
 
Cooking Akka.net and Azure Service Fabric together
Cooking Akka.net and Azure Service Fabric togetherCooking Akka.net and Azure Service Fabric together
Cooking Akka.net and Azure Service Fabric together
 
ACR + ACS + VSTS: a complete ALM pipeline with docker and azure
ACR + ACS + VSTS: a complete ALM pipeline with docker and azureACR + ACS + VSTS: a complete ALM pipeline with docker and azure
ACR + ACS + VSTS: a complete ALM pipeline with docker and azure
 
Docker & Azure
Docker & AzureDocker & Azure
Docker & Azure
 
Docker and Azure
Docker and AzureDocker and Azure
Docker and Azure
 
Come ti "pusho" il web con WebSockets: da 0 a SignalR
Come ti "pusho" il web con WebSockets: da 0 a SignalR Come ti "pusho" il web con WebSockets: da 0 a SignalR
Come ti "pusho" il web con WebSockets: da 0 a SignalR
 
Docker &amp; azure
Docker &amp; azureDocker &amp; azure
Docker &amp; azure
 
Azure service fabric: a gentle introduction
Azure service fabric: a gentle introductionAzure service fabric: a gentle introduction
Azure service fabric: a gentle introduction
 
From CRUD to messages: a true story
From CRUD to messages: a true storyFrom CRUD to messages: a true story
From CRUD to messages: a true story
 

Recently uploaded

PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
Ralf Eggert
 
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptxIOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
Abida Shariff
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
Elena Simperl
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........
Alison B. Lowndes
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Thierry Lestable
 
How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
Product School
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
Product School
 
Accelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish CachingAccelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish Caching
Thijs Feryn
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi
Fwdays
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
RTTS
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
Product School
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
Alan Dix
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
DianaGray10
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
Safe Software
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Inflectra
 
Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*
Frank van Harmelen
 
The Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and SalesThe Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and Sales
Laura Byrne
 
Key Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfKey Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdf
Cheryl Hung
 

Recently uploaded (20)

PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
 
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptxIOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
 
How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
 
Accelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish CachingAccelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish Caching
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
 
Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*Neuro-symbolic is not enough, we need neuro-*semantic*
Neuro-symbolic is not enough, we need neuro-*semantic*
 
The Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and SalesThe Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and Sales
 
Key Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfKey Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdf
 

Azure data platform overview

  • 1. Azure Data Overview …dove metto i miei dati?...
  • 2. Agenda Azure SQL Database Azure DocumentDB Azure Table Storage Azure Redis Cache Azure Search …almeno fino a ieri
  • 3. Agenda (post //build/) Azure SQL Database Azure CosmosDB (DocumentDB, MongoDB, Graph, Key-value) Azure Table Storage Azure Redis Cache Azure Search Azure Database for MySQL Azure Database for PostgreSQL
  • 6. Azure SQL Database Azure SQL Database is a relational database-as-a-service (DBaaS) hosted in the Azure cloud that falls into the industry categories of Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS). https://docs.microsoft.com/en-us/azure/sql-database/sql-database-paas-vs-sql-server-iaas
  • 7. Azure SQL Database Azure SQL Database is optimized to reduce overall costs to the minimum for provisioning and managing many databases. It reduces ongoing administration costs because you do not have to manage any virtual machines, operating system or database software.
  • 8. Azure SQL Database Azure SQL Database is optimized to reduce overall costs to the minimum for provisioning and managing many databases. It reduces ongoing administration costs because you do not have to manage any virtual machines, operating system or database software. You do not have to manage:
  • 9. Azure SQL Database Azure SQL Database is optimized to reduce overall costs to the minimum for provisioning and managing many databases. It reduces ongoing administration costs because you do not have to manage any virtual machines, operating system or database software. You do not have to manage: upgrades
  • 10. Azure SQL Database Azure SQL Database is optimized to reduce overall costs to the minimum for provisioning and managing many databases. It reduces ongoing administration costs because you do not have to manage any virtual machines, operating system or database software. You do not have to manage: high availability
  • 11. Azure SQL Database Azure SQL Database is optimized to reduce overall costs to the minimum for provisioning and managing many databases. It reduces ongoing administration costs because you do not have to manage any virtual machines, operating system or database software. You do not have to manage: backups
  • 12. Service tiers • Basic: Best suited for a small database, supporting typically one single active operation at a given time. Examples include databases used for development or testing, or small-scale infrequently used applications. • Standard: The go-to option for cloud applications with low to medium IO performance requirements, supporting multiple concurrent queries. Examples include workgroup or web applications. • Premium: Designed for high transactional volume with high IO performance requirements, supporting many concurrent users. Examples are databases supporting mission critical applications. • Premium RS: Designed for IO-intensive workloads that do not require the highest availability guarantees. Examples include testing high-performance workloads, or an analytical workload where the database is not the system of record.
  • 13. Service tiers • After initially picking a service tier and performance level, you can scale a single database up or down dynamically • Changing the service tier and/or performance level of a database creates a replica of the original database at the new performance level, and then switches connections over to the replica. • No data is lost during this process but during the brief moment when we switch over to the replica, connections to the database are disabled, so some transactions in flight may be rolled back.
  • 14. Create Azure Sql Database • Azure Portal • Azure CLI • Powershell
  • 15. Demo
  • 16. Elastic pools • SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands • Within the pool, individual databases are given the flexibility to auto- scale within set parameters. Under heavy load, a database can consume more eDTUs to meet demand. Databases under light loads consume less, and databases under no load consume no eDTUs.
  • 22. Demo
  • 23. Business continuity • Backup • Active Geo-Replication
  • 24. Business continuity: backup • SQL Database automatically performs a combination of full database backups weekly, differential database backups hourly, and transaction log backups every five minutes to protect your business from data loss. These backups are stored in geo-redundant storage • Use automated backups as your business continuity and recovery mechanism if your application: • Is not considered mission critical • Has a low rate of data change (low transactions per hour) and losing up to an hour of change is an acceptable data loss • Is cost sensitive
  • 25. Business continuity: active geo-replication • Is possible to use Active Geo-Replication to configure a database to have up to four readable secondary databases in the regions of your choice • These secondary databases are kept synchronized with the primary database using an asynchronous replication mechanism • Active Geo-Replication can also be used to provide better query performance for read-only queries to geographically dispersed users.
  • 26. Demo
  • 27. Monitoring • Metrics • SQL Database advisor • Query Performance Insight
  • 28. Demo
  • 29. Azure Database Migration Service • Using database migration service simplifies the migration of existing on-premises SQL Server, Oracle, and MySQL databases to Azure, whether your target database is Azure SQL Database, Azure SQL Database Managed Instance or Microsoft SQL Server in an Azure virtual machine.
  • 30. Azure Database Migration Service • Using database migration service simplifies the migration of existing on-premises SQL Server, Oracle, and MySQL databases to Azure, whether your target database is Azure SQL Database, Azure SQL Database Managed Instance or Microsoft SQL Server in an Azure virtual machine.
  • 32. Azure database for PostgreSQL/MySQL • Azure Database for PostgreSQL/MySQL is a relational database service in the Microsoft cloud built for developers based on the community version of open source PostgreSQL and MySQL Community Edition database engine. It provides: • Predictable performance at multiple service levels • Dynamic scalability with no application downtime • Built-in high availability • Data protection
  • 33. Demo
  • 35. Azure Table Storage Azure Table storage is a service that stores structured NoSQL data in the cloud, providing a key/attribute store with a schemaless design https://docs.microsoft.com/en-us/azure/storage/storage-dotnet-how-to-use-tables
  • 36. Table service concepts • Storage Account • Table: a table is a collection of entities • Entitiy: An entity is a set of properties (similar to a database row). An entity can be up to 1MB in size • Properties: A property is a name-value pair. Each entity can include up to 252 properties to store data
  • 37. Table entities • Table entities represent the units of data stored in a table and are similar to rows in a typical relational database table • Each entity defines a collection of properties • Entities must define the following three system properties as part of the property collection: • PartitionKey • RowKey • Timestamp
  • 42. Azure CosmosDB Azure Cosmos DB is Microsoft's globally distributed, multi-model database https://docs.microsoft.com/en-us/azure/cosmos-db/introduction
  • 44. Global distribution • Within a given region, all resources are horizontally partitioned using resource partitions (local distribution). • Each resource partition is also replicated across geographical regions (global distribution).
  • 45. Multi-model, multi API-support • The core content-model of Cosmos DB’s database engine is based on atom- record-sequence (ARS) • Atoms consist of a small set of primitive types like string, bool, and number. Records are structs composed of these types. Sequences are arrays consisting of atoms, records, or sequences. • The database engine can efficiently translate and project different data models onto the ARS-based data model.
  • 46. Multiple consistency models • It’s possible to configure the default consistency level on Cosmos DB account, and later override the consistency on a specific read request
  • 47. Guaranteed SLA • Availability: 99.99% uptime availability SLA for each of the data and control plane operations. • Throughput: 99.99% of requests complete successfully • Latency: 99.99% of <10 ms latencies at the 99th percentile • Consistency: 100% of read requests will meet the consistency guarantee for the consistency level requested by you.
  • 48. Demo
  • 49. CosmosDB: indexing • CosmosDB indexes, by default, each document’s attribute • Automatic indexing of documents without requiring schema or secondary indexes is a key capability of CosmosDB and is enabled by write-optimized, lock-free and log-structured index maintenance techniques
  • 50. CosmosDB: indexing policy • The indexing policy of each collection allows you to make performance and storage trade-offs associated with indexing • Choose whether the collection automatically indexes all of the documents or not • Choose whether to include or exclude specific paths or patterns in your documents from the index • Choose between synchronous (consistent) and asynchronous (lazy) index updates • The indexing policy can be changed
  • 51. Demo
  • 53. Azure Redis Cache • Redis is an advanced key-value store, where keys can contain data structures such as strings, hashes, lists, sets, and sorted sets. Redis supports a set of atomic operations on these data types. • Azure Redis Cache uses Redis authentication and also supports SSL connections to Redis.
  • 54. Service tiers • Basic: Single node, multiple sizes, ideal for development/test and non-critical workloads. The Basic tier has no SLA. • Standard: A replicated cache in a two-node primary/secondary configuration managed by Microsoft, with a high-availability SLA. • Premium: All of the Standard tier features, plus: • Redis data persistence: allows you to persist the cache data in an Azure Storage account • Redis cluster • Enhanced security and isolation • Reboot • Schedule updates
  • 55. Demo
  • 57. Azure Search Azure Search is a cloud search-as-a-service solution that delegates server and infrastructure management to Microsoft, leaving you with a ready-to-use service that you can populate with your data and then use to add search to your web or mobile application. https://docs.microsoft.com/en-us/azure/search/search-what-is-azure-search
  • 58. Azure Search • Full text search and text analysis • Search suggestions • Facet queries • Scoring • … • Language support • Data integration
  • 59. Service tiers • Free: A shared service, at no charge, used for evaluation, investigation, or small workloads. • Basic: Small production workloads on dedicated hardware. Highly available. • Standard: • S1 • S2 • S3 • S3 HD
  • 60. Indexers • An indexer in Azure Search is a crawler that extracts searchable data and metadata from an external data source and populates an index based on field-to-field mappings between the index and your data source. • You can use an indexer as the sole means for data ingestion, or use a combination of techniques • You can run indexers on demand or on a recurring data refresh schedule
  • 61. Indexer types • Azure Blob Storage indexer • Azure Table Storage indexer • Azure SQL indexer • Azure CosmosDB indexer
  • 62. Demo
  • 64.
  • 65. SQL IaaS vs SQL Database • Existing applications that require fast migration to the cloud with minimal changes. • SQL Server instances with up to 64 TB of storage. The instance can support as many databases as needed. • Migrating and building enterprise and hybrid applications. • New cloud-designed applications that have time constraints in development and marketing. • Databases of up to 1 TB, or larger databases that can be horizontally or vertically partitioned using a scale-out pattern. • Building Software-as-a-Service (SaaS) applications.
  • 66. SQL IaaS vs SQL Database: features • https://docs.microsoft.com/en-us/azure/sql-database/sql-database- features
  • 68. Transient fault handling Transient faults can occur in any environment, on any platform or operating system, and in any kind of application
  • 69. Transient fault handling: cloud • Many resources in a cloud environment are shared, and access to these resources is subject to throttling in order to protect the resource • Cloud environments are built using vast numbers of commodity hardware units • There are often more hardware components, including network infrastructure such as routers and load balancers, between the application and the resources and services it uses • Network conditions between the client and the server may be variable
  • 70. Transient fault handling: challanges • The application must be able to detect faults when they occur, and determine if these faults are likely to be transient, more long-lasting, or are terminal failures • The application must be able to retry the operation if it determines that the fault is likely to be transient • The application must use an appropriate strategy for the retries: • Exponential back-off • Incremental intervals • Regular intervals • Immediate retry • Randomization