Azure Database for PostgreSQL - Top Use Cases.pptx

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1. Azure Database for PostgreSQL Top Use Cases

2. Scale with ease to hundreds of nodes, with no app rewrites. Save time by running transactions and analytics in one database and avoid the costs of manual sharding. The benefits of Azure Database for PostgreSQL Build or migrate your workloads with confidence and optimized for value Enjoy maximum control and flexibility with custom maintenance windows, zone redundant high availability and additional configuration parameters for fine grained database tuning. Ultimate control and flexibility for databases Stay productive with full compatibility with community PostgreSQL and support for your favorite PostgreSQL extensions. Innovate with open-source tools and extensions Build massively scalable PostgreSQL applications Maximize performance with a fully managed Azure service Focus on your application innovation, not database management. Enjoy AI-powered performance optimization and advanced security. Single Server Hyperscale Flexible Server

3. Azure is the best destination for PostgreSQL Best of open source community along with the manageability and integration benefits of Azure Identity, security, management, and compliance Open Source Proven resilience & stability Rich feature set Fully managed Intelligent Performance Highly scalable High Availability Maximum control Integrated with Azure data ecosystem

4. Azure Database for PostgreSQL | Top Use Cases Migration Cloud-Native Applications Thanks! Cloud native section is correct. For migration section, I removed cloud native in slide 5. Also want to add a slide 4 to frame up the 2 main sections of the deck – migration and cloud native.   Flow will be:   Top use cases for Azure DB Postgres can be broken down into 2 main categories – migration and cloud native apps We’ll start with migration. 2 main migration use cases are homogeneous and oracle to Postgres. Let’s walk through each of these… Next we’ll talk about cloud native apps – 4 main types that we commonly see – transactional, geospatial, SaaS, and real time . Now I’ll walk you through each of these… Azure Database for PostgreSQL Top Use Cases

5. Migration Homogeneous Migration Oracle to Postgres Migration Cloud-native applications Migration

6. Homogeneous Migration

7. Homogeneous migration Modernize your applications with seamless migration from on-premises PostgreSQL databases to Azure Database for PostgreSQL Focus on application development, not database management, with fully managed, community edition PostgreSQL Enjoy high availability with up to 99.99% SLA Protect your data with advanced security and compliance controls Accelerate your migration using Azure Database Migration Service Offline migrations can be done via dump/restore or Azure Data Factory

8. Startup faced issues with their customer-facing, multi-tenant app on Heroku PostgreSQL (powered by AWS). It was a 3.5 TB database with 0.5 TB RAM and 3 read-replicas. Some of their customers did not want their data on AWS, costs with their Heroku database were high, and they had performance issues and were hitting a ceiling in terms of infrastructure and scale in Heroku. They chose Azure Database for PostgreSQL Single Server to reduce costs and improve performance and scalability. Successfully migrated using a combination of Azure Database Migration Service and a homegrown parallel loader script. Heroku PostgreSQL M igration to Azure Azure Public IP DNS Zone Azure Database for PostgreSQL Azure Cache for Redis Azure Kubernetes Services Azure Database for PostgreSQL Azure Kubernetes Services Azure Cache for Redis Azure Database for PostgreSQL Azure Kubernetes Services Azure Cache for Redis Azure Database for PostgreSQL Azure Kubernetes Services Azure Cache for Redis Azure Database for PostgreSQL Azure Kubernetes Services Azure Cache for Redis

9. HarvestMark , creates technology solutions that food producers, government agencies, and retailers use to track quality and boost food safety. When its former cloud provider entered the food retail market, HarvestMark had to find an alternative that would eliminate its retail customers’ concerns and migrated to Azure Database for PostgreSQL. Migration from AWS to Single Server Migrating to Azure in two hours HarvestMark provides mission-critical solutions to assess food quality and trace contamination across the supply chain. HarvestMark’s original solution ran on AWS Aurora, but when Amazon acquired a major grocery chain, HarvestMark’s customers grew concerned about conflict of interest and data security. HarvestMark chose to move to Azure because of its breadth of capabilities and services and global support. The migration was seamless, completing in two hours with no disruption to customers. 20% decreased costs and increased customer trust HarvestMark and its customers have benefitted from Azure Database for PostgreSQL’s high performance and strong security. After the migration, cloud hosting service costs decreased by 20%. “We took an instance of the database, copied it to Azure, then spun it up in the Azure managed PostgreSQL environment. It happened flawlessly in two hours.” – Todd Berg, Head of Product and Customer Success, HarvestMark Read the case study IaaS VM (s) HarvestMark Application CRUD Azure Database for PostgreSQL Master Azure Database for PostgresQL Secondary Replica HarvestMark Analytics/Reporting IaaS VM (s)

10. Shipping logistics company migrated 9 TB data from Amazon RDS to Azure Database for PostgreSQL Hyperscale ( Citus ). Database runs mission-critical aspects of their business, including freight pricing comparisons and optimizations through order analysis and shipping tracking analytics. Faced issues with Amazon RDS scalability and performance of analytics rollups. Hyperscale ( Citus ) was a great choice for the mixed transactional/analytical workload with heavy use of rollup queries and scheduled processing jobs. Hyperscale ( Citus ) enables them to future-proof their database, as they project 50%+ annual growth. Migration from AWS to Hyperscale ( Citus ) Azure Database for PostgreSQL Analytics and pre-aggregation Data normalization Internal Applications 3 rd party services End users Application Servers Redis cache Data ingest pipeline

11. Oracle to Postgres Migration

12. Oracle to Postgres Migration PostgreSQL has become a primary destination for Oracle workloads Avoid lock-in with open-source PostgreSQL – not a forked version Benefit from cloud scale, built-in intelligence, and integration with the Azure ecosystem Lower total cost of ownership (TCO) Similarities between Oracle and PostgreSQL ease migration effort Leverage Ora2PG, a free tool, to automate most schema and app changes Learn more with our detailed migration guide

13. Chevron, one of the world’s largest oil and gas companies, chose Azure Database for PostgreSQL to replace Oracle in its 12 Documentum environments worldwide. Documentum Migration Migration to Azure Database for PostgreSQL Documentum is a critical application for engineering and operational workflows at Chevron, storing important information including oilfield maps and engineering drawings When OpenText decided to move their Documentum content management platform away from Oracle to optimize on PostgreSQL, Chevron turned to Azure. Thanks to a strong partnership across Microsoft, OpenText, and Chevron, they successfully deployed the OpenText solution on Azure Database for PostgreSQL and migrated the data from on-premises Oracle to Azure Chevron has migrated 12 instances across the globe to Azure Database for PostgreSQL Azure Database for PostgreSQL Azure DevOps Azure Files Hub Vnet Spoke Vnet Node 3 Node 2 Node 1 User Access CD CI On-Prem ExpressRoute

14. Cloud-native applications Transactional applications SaaS applications Geospatial aware applications Real-time applications Cloud-native applications

15. Transactional applications

16. Transactional applications Why use Azure Database for PostgreSQL for transactional apps? Robust support for many data types, including time-series data and semi-structured data with JSONB Postgres transactions are ACID (Atomicity, Consistency, Isolation, and Durability) compliant, ensuring strong consistency for apps that must be always up to date Enjoy high throughput OLTP via Hyperscale ( Citus ), for apps with thousands or tens of thousands of transactions per second. Benefit from cloud scale, built-in intelligence, advanced security and compliance, high availability, and integration with the Azure ecosystem

17. Banking Platform Building a cloud-native banking platform Finxact provides banks with a modern approach to their system of record – the core services that handle deposits, loans, and other banking functions. Their cloud-native architecture ensures they can meet the demands of modern banks – massive scale, performance, high availability, and ability to meet regulatory requirements. Finxact leverages managed open-source services, including Azure Kubernetes Service and Azure Database for PostgreSQL. Benefits of Azure Database for PostgreSQL Azure Database for PostgreSQL is used as a relational data store for Finxact’s core processing service. They leverage JSON data types, thanks to Postgres’ support for JSONB , enabling a flexible data model. Service availability is crucial. Azure Database for PostgreSQL is backed by a 99.99% SLA, but Finxact also deploys their database across multiple Availability Zones to provide an even higher level of availability. “The availability of open-source services on Azure enabled Finxact to leverage the most advanced solutions to support our customers’ business needs at massive scale.” – Frank Sanchez, CEO, Finxact Read the case study Azure files Customer 1 Public Subnet xxxxx /xx Azure Bob Storage Azure Database for PostgreSQL OLAP Azure Database for PostgreSQL OLAP Azure files INTERNET Azure DNS Replica Replica Replica Public Subnet xxxxx /xx Public Subnet xxxxx /xx Bastion Host AKS Namespace 1-n Bastion Host Namespace 1-n Bastion Host Namespace 1-n Availability Zone 1 Availability Zone 2 Availability Zone 3 Azure Public Load Balancer Customer n Public Subnet xxxxx /xx Azure Bob Storage Azure Database for PostgreSQL OLAP Azure Database for PostgreSQL OLAP Customer 1 Public Subnet xxxxx /xx Azure Bob Storage Azure Database for PostgreSQL OLAP Azure Database for PostgreSQL OLAP Public Subnet xxxxx /xx Public Subnet xxxxx /xx Bastion Host AKS Namespace 1-n Bastion Host Namespace 1-n Bastion Host Namespace 1-n Availability Zone 1 Availability Zone 2 Availability Zone 3 Azure Public Load Balancer Customer n Public Subnet xxxxx /xx Azure Bob Storage Azure Database for PostgreSQL OLAP Azure Database for PostgreSQL OLAP

18. Postgres powers connected passenger cars Car manufacturer had monolithic existing system to power their connected vehicle services. Oracle history and open source preference led them to choose PostgreSQL as they moved to the cloud. Modernized by replacing their old system with a cloud-native, microservices based system powered by Azure Database for PostgreSQL and Azure Kubernetes Service. Hundreds of AKS clusters power dozens of applications users interact with in passenger cars, including navigation, entertainment, and a virtual assistant. Postgres stores almost all backend data. For example, Postgres databases store the mapping of which customers have subscribed to each service offered by the platform - a cornerstone of the overall system. Azure Database for PostgreSQL provides advanced security for sensitive data, high availability for mission-critical services, and cloud scale. Connected Vehicle Backend Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service Azure Kubernetes Service

19. Robert Bosch GmbH is an engineering and technology company which creates products and services across Mobility Solutions, Industrial Technology, Consumer Goods, and Energy and Building Technology. With the goal of saving lives, Bosch turned to Azure to help build a wrong-way driver warning service. Vehicle Safety App Keeping drivers safe using data As they set out to solve the problem of drivers going the wrong way on highways, Bosch knew they could not compromise when it came to real-time speed and precision of location data. Bosch built a solution using Azure managed services, including Azure Database for PostgreSQL, Azure Kubernetes Service, Azure Cache for Redis, Azure Databricks, and more. Leveraging PaaS services freed Bosch’s small development team from time spent managing infrastructure. Building a cloud-native application Azure Database for PostgreSQL delivers a highly available relational database that requires almost no administration, saving them time and costs. Azure Database for PostgreSQL seamlessly integrates with services like Azure Kubernetes Service and Azure Databricks. The solution ingests 6M requests per day from devices emitting GPS data and from partner systems. By running on Azure, Bosch improved the average time to calculate whether a driver is going the wrong way to 60 milliseconds. Wrong-way driver warning services Azure Kubernetes Service Kafka on Azure HDInsights Push servicer Virtual network security Virtual API Management Virtual Key Vault Azure Data Explorer Azure Monitor Azure Cache for Redis Azure Database for PostgreSQL Azure Databricks Continuous Map updates Azure Container Registry Azure App Service Azure App for Containers Azure AD authentication Read the case study

20. Build apps to facilitate retail transactions Azure Database for PostgreSQL is often used in retail applications; for example, storing point of sale data, facilitating e-commerce transactions, or powering inventory management systems. Here, a large grocery chain uses Azure Database for PostgreSQL for an app that distributes data on prices, promotions and product images to checkout tills in around 4,000 stores. Updates happen in near real time, and cannot have a high impact on the network, as the network is used for many different purposes, including card payments. There must be consistency across stores even while updates are being made centrally to prices in the PostgreSQL database. A mechanism similar to Kafka offsets was used to achieve consistency, and PostgreSQL was selected as it supports this. The current offset is a pointer to the last record sent to the device in the most recent poll. In-store devices poll APIs for updates using offsets. Updates up to a maximum offset are sent to a server in each store which, in turn, distributes the updates to tills. Updates to price and product data are published to a HTTP endpoint. The data is inserted into the PostgreSQL database, with an offset assigned. Retail Store App Azure Database for PostgreSQL Azure Kubernetes Service API Management Services Application Gateway On-Premises Tills connect to a server in each store

21. Azure Swiss Re , one of the world’s largest reinsurers, uses Azure PaaS services, including Azure Database for PostgreSQL, to power a digital transformation that includes the modernization of business-critical financial systems. Java App Modernization Simplifying development with Azure Swiss Re has built new Java-based financial apps and migrated existing ones using Azure Spring Cloud, a fully managed infrastructure for Spring Boot applications. Azure supports the company’s strict security and regulatory requirements, and allows developers to develop and deploy solutions faster. The team can store and retrieve information in Azure Database for PostgreSQL with a simple Spring Data JDBC call. For persistency, any data managed in their microservices is stored in PostgreSQL. Azure Database for PostgreSQL and Azure Spring Cloud enable Swiss Re’s developers to focus on writing apps, while Azure takes care of scaling, security, compliance, and high availability. Read the case study Azure Database for PostgreSQL Database Azure Key Vault Key Vault Azure AD Tenant Business User Cloud fair Gateway Azure Spring Cloud Spring Cloud Gateway Spring Boot Back in Servers Spring Boot Azure Monitor Applications Insights Log Analysis Workspace Azure Storage Static Content

22. Build highly scalable, enterprise-grade apps with Hyperscale ( Citus ) Government agency responsible for a country’s tax administration built their electronic invoice and tax payment settlement systems on Azure Database for PostgreSQL Hyperscale ( Citus ). Chose Hyperscale ( Citus ) because of a preference for open source and existing Postgres skillset, along with a need for scale – one app is ~1PB and data volume is expected to grow 50% over the next 2 years, with thousands of concurrent users. Performance and high availability are key for mission-critical apps that serve as primary sources of information for many teams across the agency. Data model consists of 10-15 large tables, with an identifier for invoice, allowing for JOINs. Invoice ID is used as central distribution key. Created monthly partitions as most queries have a time dimension. Electronic Invoice Application XML Validates Client Invoice Taxpayer Query process Metadata Taxpayer Data Extracted in process Databricks process Azure Database for PostgreSQL Taxpayer’s statement weekly ADLS Event Kafka Event Kafka on Azure HDInsight

23. Geospatial aware applications

24. Geospatial aware applications Why use Azure Database for PostgreSQL for geospatial aware apps? Azure Database for PostgreSQL is often used for apps with a location component – for example, route optimization, fleet monitoring, and supply chain management Robust support for many data types, including time-series data, JSONB, and geospatial data with PostGIS Postgres transactions are ACID (Atomicity, Consistency, Isolation, and Durability) compliant, ensuring strong consistency for apps that must be always up to date Enjoy high throughput OLTP via Hyperscale ( Citus ) Benefit from cloud scale, built-in intelligence, advanced security and compliance, high availability, and integration with the Azure ecosystem

25. Helsinki Region Transport Authority (HSL) is responsible for over 1 million public transportation journeys per day in Finland, across bus, train, Metro, tram, and ferry services. HSL replaced its on-premises Postgres solution with Azure Database for PostgreSQL Hyperscale ( Citus ), dramatically improving performance and reducing costs. Transportation Logistics Challenges monitoring a complex network HSL employees lacked access to real-time location and geographical data on vehicles in their network, making it difficult to monitor and enforce whether operators were running on time and on schedule. They initially built a solution on-premises, but quickly ran into scale and performance challenges. The system was ingesting GPS data every second for over 2,000 vehicles, and as the database grew, so did query processing time. Better performance with 50% lower costs In less than a month, HSL replaced their on-prem Postgres database with Hyperscale ( Citus ) on Azure. Postgres’ rich support for time-series data and geospatial data with PostGIS made it a great fit for vehicle information such as location and arrival times, and Hyperscale ( Citus ) easily handles high volumes of reads and writes in near real-time. Partitioning their data vertically based on time stamps and sharding horizontally by bus ID resulted in improved performance, with queries now able to be processed instantly. Along with better performance, moving to Hyperscale has reduced operational costs by over 50%. “It was a whole different environment once we moved to Hyperscale. Queries that often took up to 10 minutes with the old system are now processed instantaneously.” – Sami Räsänen , Product Owner and Team Lead, HSL Read the case study Pulsar microservices Azure Cache for Redis Azure Database for PostgreSQL Hyperscale ( Citus ) Azure Database broker (mqtt.hls.fi) CANCELLATIONS SERVICE ALERTS JORE pipeline Azure Database Azure SQL Database server UI

26. Efficiently track packages and deliveries at scale Event-driven architecture using Azure Event Hubs collects tracking data and distributes it to business intelligence systems that power reporting. Microservices running on Azure Kubernetes Service grab tracking data from Event Hubs and perform calculations – for example, package lifecycle. With PostgreSQL’s JSONB support, data and logic can be stored in the same document. Calculations like package lifecycle don’t have to be made every time the package is scanned, and less data is stored and archived, lowering storage costs. Azure Database for PostgreSQL provides scale, high availability, and rich support for geospatial data with the PostGIS extension. Package Tracking Azure Kubernetes Service Legacy central database Azure Database for PostgreSQL Azure Event Hub Azure ExpressRoute Scan Server On-premises Event ingestion Parcel Processing Parcel Master Processing Master data ingestion Event store maintenance Azure Load Balancer

27. For leading energy company BP, safety is top priority. They chose Azure Database for PostgreSQL Hyperscale (Citus) to build a solution to help them meet security and safety requirements by tracking building access in real-time. Building Security Management Tracking geospatial data in real time The ability to track spatial data was crucial to the solution, which involved tracking badge access and location in real time. PostgreSQL was chosen for its strength in working with location-based data. BP needed a fully read-write database that could scale. The solution needed to ingest data in real time while serving analytics and BI with sub-second response time. Hyperscale (Citus) was a great fit for these requirements. Data insights to ensure security and safety BP built a solution using Azure Data Factory and Event Hubs for data ingestion, Azure Stream Analytics to transform real-time data into insights, and Power BI to deliver data insights via dashboards. With Hyperscale (Citus), the database delivering a customer-facing experience also became the system of record. The system can handle multiple workloads (OLAP and OLTP) at speed. Operational overhead is reduced by using a fully managed, open source Postgres database Event Hub Azure Stream Analytics Power BI Azure Data Factory Azure Database for PostgreSQL Hyperscale ( Citus ) Arc GIS Enterprise Azure Storage SQL Storage Koop JS

28. Producers Cloud9, a top esports competitor, relies on data and analytics to inform the way their players train, strategize, and compete. Their Game Insights Platform, built on Azure, is a great example for companies across industries seeking to harness data for business intelligence. case study here Gaming Insights Platform Data as a competitive advantage Using Azure, Cloud9 built a real-time dashboard to help coaches and players track wins, strategies, matches, and trends over time. Cloud9 chose Azure Database for PostgreSQL as the primary database to store positional information because of PostgreSQL’s rich geolocation analysis features. A machine learning model analyzes videos of gameplay and identifies interesting parts, storing the output in Azure Database for PostgreSQL. By using a fully managed Postgres service, Cloud9 gains intelligent performance, security, and scalability without having to manage the database themselves. Azure Database for PostgreSQL seamlessly integrates with services like Azure Functions and Power BI. “We started by asking, what is the most important data we can act on that is not otherwise available to us? Then we built a pipeline on Azure to automate the process of finding it, capturing it, and making it usable.” – Mike Downey, Director of Sports Technology, Cloud9 Read the case study and watch the video to learn more Azure Monitor Azure Pipelines Azure Container Registry Docker Pull Docker Push Game data Event processing Azure Ingestion Storage Containers Microsoft Power BI Azure Key Vault Azure Container Instances Azure Database for PostgreSQL Azure Functions Azure Queue Storage Azure Blob Storage Azure Blob Storage Computer Vision

29. SaaS applications

30. SaaS applications Why use Azure Database for PostgreSQL for SaaS apps? Enjoy high throughput OLTP via Hyperscale ( Citus ). Many SaaS apps are multi-tenant, which make them a great fit for sharding with Hyperscale ( Citus ). The tenant ID makes for a natural distribution key. JSONB support makes it possible to combine relational data with semi-structured data types. Benefit from cloud scale, built-in intelligence, advanced security and compliance, high availability, and integration with the Azure ecosystem. Hyperscale ( Citus ) can be a good choice to power workloads where High concurrency: 50+ end users querying the database at one time, along with concurrent ingest. Fast growing app: database is hundreds of GBs and growing, SaaS app has thousands of customers and hundreds of thousands of users. Tenants need to be kept separate, but you also want the ability to run cross-tenant queries for internal monitoring.

31. Build scalable, multi-tenant sales and marketing platforms Common solutions include email marketing and ecommerce platforms Multi-tenant architecture often with one database server per customer Easily scale during peak times (e.g. holiday season) PostgreSQL’s extensibility and support for many types of data (e.g. JSONB , time-series) make it a flexible choice Azure Database for PostgreSQL provides reliability, high availability, and performance necessary to meet customer expectations Read replicas can help improve performance and scale of read-intensive workloads e.g. BI workloads for reporting Sales and Marketing Automation Private servers Cloud Controller Service Manager Service Broker Core Resource Group Backing Services Resource Group Applications VNET Peering Connection Applications ResourceManager , Database

32. PTC creates digital solutions for Industrial IoT that help manufacturing, service, and engineering companies connect, monitor, analyze, and act on data in new ways . IoT Development Platform Industrial IoT Platform PTC’s ThingWorx solution is an Industrial IoT platform with tools to help businesses connect assets, build apps and augmented reality experiences, analyze IoT data, manage connected systems, and more. Common use cases include remote asset monitoring, predictive maintenance, remote service, and equipment optimization. Architecture and database Thingworx is a multi-tenant SaaS app. A distributed architecture allows for global management of consolidated statistics and KPIs, while local managers get focused, real-time information on their specific locations. PTC customers can choose their preferred database, and Azure Database for PostgreSQL is a popular choice. High availability, security, and performance are key requirements in the Industrial IoT space. Virtual Network Azure Database for PostgreSQL Experience Repository Experience Repository

33. Global customer-facing web app App helps customers book car rentals – choose car, schedule and manage rentals. Java web app (Spring Boot) uses Azure Database for PostgreSQL Single Server and Azure Kubernetes Service. App will have multi-tenant architecture as car rental service expands globally, with regional deployments. Azure Database for PostgreSQL chosen due to existing Postgres skillset and open source preference, in addition to PaaS benefits like high availability. Security is a top priority as the app handles confidential data, such as PII and internal business data. Customer managed key encryption was a requirement. Car Rental App Corporate network, Data center External access Other external data centers InternetZone Container Registry InternetZone Azure Load Balancer Azure InternetZone Azure Load Balancer Container Registry VNet Microsoft KeyVault ServiceEndpoint Microsoft SQL ServiceEndpoint Azure Kubernetes Service VNet Microsoft KeyVault ServiceEndpoint Microsoft SQL ServiceEndpoint Azure Kubernetes Service

34. Real-time applications

35. Real-time applications Why use Azure Database for PostgreSQL for real-time apps? Robust support for time-series data as well as JSONB, making it possible to combine relational data with semi-structured data types Hyperscale ( Citus ) offers high throughput OLTP as well as sub-second performance leveraging parallelism Benefit from cloud scale, built-in intelligence, advanced security and compliance, high availability, and integration with the Azure ecosystem Hyperscale ( Citus ) can be a good choice to power workloads where: Mixed workloads with transactions and analytics (e.g. UPDATE, DELETE in addition to INSERT/COPY) High concurrency: 50+ end users querying the database at one time, along with concurrent ingest Smaller datasets (< 10 TB) End users need to ask questions with many parameters (i.e. query with many different column filters)

36. BNY Mellon is the world’s largest custodian bank and asset servicing company. Focused on helping their clients use data insights to make better decisions, BNY Mellon turned to Azure Database for PostgreSQL Hyperscale to build an integrated data and analytics platform. Real-Time Operational Analytics Helping clients make data-driven decisions BNY Mellon’s Distribution Analytics solution helps asset managers understand US investment market dynamics and forecasts based on predictive models. Terabytes of structured, semi-structured, and unstructured data, from sources on-prem and in multiple clouds, are unified in Azure. Azure Database for PostgreSQL Hyperscale ( Citus ) is used for both transactional and analytical data processing. Benefits of Hyperscale ( Citus ) Azure Database for PostgreSQL provides a fully managed, highly available, and flexible database that allows BNY Mellon’s team to leverage existing Postgres skills. Hyperscale ( Citus ) enables them to automatically scale out multiple instances of the data to optimize READ and WRITE operations, using parallel processing. PostgreSQL’s support for JSONB lets them work with structured and unstructured data types. Watch the video to learn more Azure Database for PostgreSQL Metadata service Sales Analytics service Query service Distribution Analytics service Azure Cache For Redis On-premises sales and redemption data Consul DVAcontainer Extract Service Slice service Load service Input.slice queue Input. Slice queue Dispatch service Disk On-premises security Master information Third-party SaaS services Distribution Analytics users interface in another cloud

37. Provide low latency interactive dashboards for end user queries Data from various sources (e.g. sales, marketing, support) gets ingested into Hyperscale ( Citus ). Azure Databricks or Azure Data Factory is used as ETL engine to clean and transform data. Final datasets exposed to end users via interactive, real-time analytics dashboards, such as Metabase or Power BI. Query parallelism and flexibility in creating indexes can lead to huge performance gains. Store semi-structured data using JSONB data type. JSONB can provide 6-7x compression. Scale each node’s compute and storage independently to optimize costs. Horizontally scale with no downtime. Read this blog to learn more Customer Facing Dashboards Azure Databricks Spark Cluster Sales Data User Events Data Marketing Data Hyperscale (Citus) on Azure Database for PostgreSQL Analytics Data Store Metabase Dashboards Data Transformation & Cleansing

38. C.H. Robinson solves logistics problems for companies across the globe and across industries, from the simple to the most complex. With $21 billion in freight under management and 19 million shipments annually, they are one of the world’s largest logistics platforms. They provide a bidding marketplace between shipping fleet providers and customers seeking to ship products and chose Azure Database for PostgreSQL Hyperscale ( Citus ) to power their pricing engine workload. Pricing Engine Mission-critical workload faced limits on-prem C.H. Robinson leveraged an on-prem Postgres database to power their mission-critical pricing engine. Using a proprietary reinforcement learning engine, they use data to predict pricing for new bids. PostgreSQL’s JSONB support was critical, as they store large volumes of semi-structured data. When they faced scale and performance issues with the on-prem Postgres database, they migrated to Azure Database for PostgreSQL Hyperscale ( Citus ). Benefits of Hyperscale ( Citus ) Hyperscale ( Citus ) gave them increased scale and a 1.5x performance improvement over single-node Postgres, while allowing them to simplify their architecture by combining OLTP and OLAP workloads. Additionally, the engine powers customer-facing dashboards which surface bids, pricing history, deals won, and revenue metrics. Data scientists can also use this engine to perform dynamic quote modeling to drive informed decision-making. Loads/Quotes Topic Win Matching Topic Win Matching App Database API ELT Process Azure Database for PostgreSQL Hyperscale ( Citus ) Legacy Apps DS Ad-Hoc Queries ELT Retry Process Loads/Quotes Retry Topic Loads/Quotes Retry Topic Other Bidding Apps Future Applications API History Topic

39. Build IoT apps that scale to millions of devices Enable your IoT app to query both historic events and the current state of devices, using both UPDATEs and JOINs. Relational databases like Postgres give you relational features such as JOINs. Hyperscale ( Citus ) lets you ingest and query concurrently and at scale. It’s a good fit for apps with a need for concurrency, real-time, high-throughput ingest, and fast query response times. Device ID often used as sharding key. Ingest and process IoT telemetry in real time to power event-driven applications and dashboards. With Hyperscale ( Citus ), we’ve seen customers with databases in the tens of TBs, as well as those with millions of devices. Tests with Hyperscale ( Citus ) have simulated 5M devices with 2B measurements/hour with P95* <500ms for non-hierarchical queries and P95 < 2s for hierarchical queries. IoT Applications Ingress ASA Egress IoT Hubs Service Bus IoT Microservices Indexers Query Processors PostgreSQL Hyperscale Cluster Company Workers Structured Instance Events Ingestion Query Life Cycle Events Microsoft Power BI PG Bouncer *P95 – query performance in 95% of cases

40. Microsoft