MongoDB - Quantificare il vantaggio di business


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Quali impatti ha la scelta di un database sul nostro business? Attraverso dei casi d'uso vi mostreremo come la scelta di MongoDB ha cambiato il business di alcune aziende.

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  • Database typically deeply embedded in a tech stack. Users never really get to see it – so does the choice really matter, and can you measure what it gives you
    Give you specific examples – will explore these and others in more detail later

  • Examples: Deliver apps that weren’t previously possible – build in 3 months what couldn’t be built in previous 8 years
  • Drive 80% cost reduction
  • Why is the database so important
  • At the heart of the change is data, and the role in plays in modern apps
    • 90% of the world’s data was created in the last two years
    • 80% of enterprise data is unstructured
    • Unstructured data growing 2x faster than structured
    In the digital economy, data is the raw currency. How you stores, manages, analyzes and uses data has a direct impact on the your success.
  • RDBMS was only real database option up until relatively recently – great for structured data, but no good for multi-structured, polymorphic data generated by todays applications

    Even historically, the RDBMS only held 15-20% of an organisation’s information assets. We now have the tools and technologies that can harness the other 80%
  • To summarise the requirements of a modern database to meet needs of a modern apps, you need:
    Flexible data model to store multi-structured, rapidly changing data
    Run rich analytics
    Need to support agile dev methdologies to accommodate constantly changing requirements
    Scalable on commodity hardware to handle growth
    Cannot sacrifice enterprise quality – uptime or security
  • Over 100k production deployments who have adopted MongoDB to support these requirements – across a wide range of use cases
  • Lets start to drill into some examples of where the choice of database has had a tangible business outcome – start with TTM
  • MetLife is one of the world’s largest insurance companies.
    Masses of data around 100m customers and 100+ products and policies stored in 70 different source systems
    Wanted to bring that together to create single view for better customer experience when they called into a CSR. Also identify risk of churn and cross-sell, upsell

    Started project back in 2005, most recent initiative working on a RDBMS had taken 2 years, cost $10ms, still not successful. Developing a single schema that could take data from 70 systems wasn’t possible, as soon as changes to source, then schema broke
    Realised needed to change assumptions
    Started with MongoDB – built a poc in 2 weeks, and went into production 3 months later
    Key was flex schema
    Used MongoDB subscription gaves access to expertise used in dev phase to get them on the right path, and stands with them in production. Also use MMS for proactive monitoring and alerts so can maintain uptime

  • Launching an app in the worlds 2nd highest population – 1.3bn (17%), need to know it can scale
    Hike is India’s fastest growing messaging app – joint venture between Bharti and Softbank – 2 huge multinational companies
    Using MongoDB, scaled to over 15m users in 9 months. Key for them
    – MongoDB sharding and replica sets for scale and availability
    – MongoDB query framework for running complex analytics
    – MongoDB subscriptions for support, best practices and advanced security features
  • Final example in this section
    One of world’s largest telecoms providers with operations across Europe and Latam
    Much like Metlife, needed to build single view of their subscriber
    Specifically focused on landline, mobile, IPTV, app store and location- based services. Like many telcos, these services all had their own databases, making it impossible to get real time view of the subscriber

    Started initial dev on Oracle database.
    To build single view, needed a schema with 20 separate tables, typical operations requiring 35 separate JOINs. Auth alone was an operation that joined 5 tables
    Didn’t scale. Also loads to EDW were taking too long. 3 versions of the prototype over 15 month period

    Knew needed a new approach – evaluated MongoDB
    More flex data model meant could represent data in 5 collections, rather than 20 tables, most operations hit 1 or 2 collections at most

    They engaged early, used MongoDB Dev Subscriptions and Training to get them on right path
    Result – compressed dev cycle by 4x – used 50% of the dev resource. Storage reduced by 4x, query latency by 10x
  • Looked at time to market – look at perf and availability – has direct impact on customer experience
  • one of the world’s leading relationship service providers,
    relies on compatibility matching system to introduce potential partners,
    relies on analyzing a user’s traits and preferences. 

    To run matching across their entire use base taking 15 days on RDBMS – too long.

    Looked for alternatives – found using flex data model and rich queries, along with ability to shard to scale out, they could reduce matching time to 12 hours – 95% improvement
    Use combination of consulting and subscriptions to put dev on right path and simplify their operations
  • Maintain vehicle history database – enables potential buyers of used cars to verify provenance of a vehicle – service history, previous owners, damage reports

    Originally built on a K/V store,
    As database grew, hit scalability limits. Also very complex to run DR across multiple DCs, impact service availability

    So evaluated a range of solution – chose with MongoDB
    Couldn’t tolerate eventual consistency – added to much complexity to their apps
    MongoDB met their scalability requirements, got a cluster with around 50 nodes, distributed across 2 datacenters, serving 12.5bn docs – 10x faster than their existing K/V store
  • final example in this section
    ADP one of the world’s leading HR and payroll outsourcing solutions provider,
    Wanted to extend access to their core HR apps to mobile devices
    Uptime and functionality were critical
    After extensive evaluation of multiple databases, ADP selected MongoDB
    MongoDB’s document model and dynamic schema made it fast for developers to build the application.
    Maintain functionality due to rich query model
    Replica sets and MMS application give them service continuity – through replication and proactive monitoring and alerting
  • Final section – driving cost out
  • Slide 25 –
    Tier1 bank migrated reference data mgt app from RDBMS to MongoDB

    App had a master copy of the data generated in New York, replicated to 12 global data centers consumed by local apps, and used for reconciliation and reporting. But took up to 36 hours for data replicate because of the complexity of the schema. Bank was operating on old data – hit with fines. Also high licensing and maintenance costs, high expensive h/w.
  • Moved to MongoDB, using built in DC-aware replication, replicate across DCs in minutes
    Moved expense model from capex to opex

    In total, bank estimates saved $40m over 5 years

  • Another RDBMS user, Shutterfly, built platform supporting digital photo products on Oracle.

    Need to release new products to market faster, run deeper analytics, reduce cost.
    Trying to represent complex objects in Oracle wasn’t scaling, so looked at alternatives, chose MongoDB

    Reduced dev sprints from months to weeks. They’ve simplified their code base by eliminating ORM – improved average query response time by 9x
    Reduced cost – 80% lower than Oracle

    In addition to the technology, use MMS for proactive monitoring. Speeds up issue resolution as all key metrics can be accessed by support team at MongoDB, means cut down going backwards and forwards with logs
  • MongoDB subscription – bundle of services and features designed to make you successful faster

    Typically value starts before production, because consultative support can provide assistance in schema design, data migration H/W selection, sharding, testing. Then there with you in production – more than just break/fix – regularly check in to proactively address issues. Access to training and consulting

    Get access to advanced security features, including Kerberos auth, LDAP integration and auditing for compliance

    Also got access to Automation, DR and Monitoring
  • MMS is the application to manage your MongoDB environment – ops teams love
    Automation – provision anything from single replica sets to large sharded clusters spanning regions in a single operation. Not just the database, provision underlying h/w on prem and in the cloud. Used to automate online upgrades – again, click of a button. Tech preview

    MMS Backup provides DR – only solution providing continuous incremental backup, point in time recovery and snapshots of sharded clusters

    MMS Monitoring – tracks over 100 variables including operations counters, queues, system utilisation. Can create alerts – sent to pagerduty, hip chat, email and text

    MMS is a free hosted service provided by MongoDB – so you connect your systems to it. Or you can deploy on-prem as part of a subscription

  • How we hAlso dedicated consulting and training service delivered remotely or on site – brings MongoDB expertise to your project
  • Now have over 1k customers of these services – includes nearly 1/3 of Fortune 100, can see strong use across multiple industry sectors
  • What I hope I’ve demonstrated is that a database can deliver quantifiable biz advantage

  • What I hope I’ve demonstrated is that a database can deliver quantifiable biz advantage

  • – final example is telecoms operator Orange who operate mainly in UK, Germany and France
    Running product catalog on a RDBMS, on-premise, but growth in users and content meant started to look to new app, DB and hosting capabilities
    Decided to move DB layer to MongoDB and rehost environment to AWS where they could scale on demand and take advantage of lower pricing. Architecture of AWS fits well with MongoDB. Saved $2m
    Key to success was working closely with MongoDB engineers to optimize app design and production playbooks
  • Applications are getting much more sophisticated – Handle and aggregate mobile, social, sensor data and real-time analytical applications are essential for remaining relevant.
  • Semi-structured and unstructured data does not lend itself to be stored and processed in the rigid row and column format imposed by relational databases, and cannot be fully harnessed for analytics if stored in BLOBS or flat files. It is critical to select a database that can not just store complex data, but also enables rich query and analytics capabilities in order to increase business visibility across a variety of data assets.
  • Traditional s/w dev methodologies predicated on defining all the requirements at start of the project – any changes often meant changing the data model – so things get very slow. Reality is todays apps are developed much more iteratively where requirements change frequently, using agile methodologies. Need a database that can handle those changes, without having to change your schemas. Can do it in dev, and do it production, without downtime
  • Rise of commodity servers and cloud computing changes the cost model of infrastructure, companies keen to ride that economic curve. RDBMS designed for scale up, rely on ever larger hardware. Can scale them out, takes huge engineering efforts and lose lots of benefits of relational model – denormalise, lose JOINs, lose trx that cross nodes

    To take advantage of the economies, you need databases that can can scale out natively, with in built replication so they can take advangtage elasticity of the cloud and handle fact commodity servers do fail
    Need to ensure security of the data
  • MongoDB - Quantificare il vantaggio di business

    1. 1. Quantificare il Vantaggio Competitivo: Il valore della scelta del database #mongodb
    2. 2. Un database può davvero fornire un vantaggio competitivo quantificabile?
    3. 3. Costruire in 3 mesi… quello che non è stato fatto negli 8 anni precedenti
    4. 4. Accelerare l’ingresso nel mercato di 4 volte con il 50% di risorse in meno
    5. 5. Servire i clienti 10 volte più velocemente
    6. 6. Ridurre i costi del 80% aumentando le performance di 9 volte
    7. 7. Requisiti delle Applicazioni Moderne
    8. 8. I Dati sono Cambiati
    9. 9. Gli Strumenti di Ieri per i Dati di Oggi?
    10. 10. Modello dei Dati Flessibile Requisiti di un Database Moderno. Query Estese Scalabile Schema Dinamico Cresce Velocemente Indici Secondari, Aggregazioni, Search Agile Innovazione Continua Pronto per l’Enterprise Sicuro e Affidabile
    11. 11. MongoDB: Potenzia le Applicazioni Moderne Big Data Cataloghi Prodotti e Asset Sicurezza e Frodi Internet of Things Database-as-a- Service Applicazioni Mobili Customer Data Management Vista Unificata dei Clienti Social & Collaborazione Content Management Intelligence Agencies Top Investment and Retail Banks Top Global Shipping Company Top Industrial Equipment Manufacturer Top Media Company Top Investment and Retail Banks
    12. 12. Guadagnare Vantaggio Competitivo: Andare sul mercato più velocemente
    13. 13. In servizio in 3 Mesi Dati aggregati da 70 sistemi sorgenti per creare una vista dei clienti singola “Introdurre tecnologie come MongoDB ai nostri team di sviluppo…. Li potenzia per rilasciare in qualche mese il lavoro per il quale normalmente ci vogliono anni.” Gary Hoberman, CIO and Senior Vice President, Regional Application Development, MetLife
    14. 14. 15m Utenti in 9 Mesi • App di messaggistica con il più alto tasso di crescita in India • Requisiti: – Scalare velocemente, eseguire analitiche real-time, assicurare SLAdi classe Enterprise • Cresciuta a 15m di utenti in solo 9 mesi con MongoDB – MongoDB sharding e replica sets – MongoDB query framework – MongoDB Enterprise per il supporto, best practice e funzionalità di sicurezza avanzata
    15. 15. 4x più veloce sul Mercato • Crea un singolo profilo attraverso multipli servizi • Hanno provato Oracle, ma non scalava • Passati a MongoDB – Fatto il progetto 4 volte più veloci e con il 50% del team di sviluppo. – Latenza 10 volte inferiore
    16. 16. Migliorare la Customer Experience: Nuovi livelli di Performance e Affidabilità
    17. 17. Compatibility Matching System usato per effettuare il match di potenziali partners “Con il nostro sistema SQL, l’intero set del profilo utente era memorizzato in ogni server, con un impatto sulle performance e con un limite alla nostra capacità di crescere orizzontalmente. MongoDB supporta la scalabilità necessaria al nostro business e ci permette di effettuare i match in real-time.” Thod Nguyen, CTO, Match del 95% più veloci
    18. 18. 10 volte più veloce “Sostituire I nostri database legacy con MongoDB ha permesso di prepararci per la crescita futura. MongoDB migliora la nostra capacità di rispondere alle nuove esigenze dei nostri clienti evdi crescere il nostro database di veicoli storici..” Joedy Lenz, CTO, CARFAX
    19. 19. Estende le applicazioni di HR ai dispositivi mobili Perché MongoDB – Agilità per gli sviluppatori: il modello a documenti e lo schema dinamico – Funzionalità: sistema di query potente – Alta disponibilità: Replica set Risultati – Continuità di servizio: MongoDB Enterprise & MMS Sempre Disponibile
    20. 20. Abbattere i Costi
    21. 21. Tier 1 Bank $40m Savings Golden Copy Batch Batch Batch Batch Batch Batch Batch Batch Reference Data Management • Fatto con RDBMS • Fino a 36 ore per replicare tutti i dati Impatti • Dati quasi statici • Alti costi di licenza • Hardware costoso
    22. 22. Real-time Real-time Real-time Real-time Real-time Real-time Real-time Real-time Migrato a MongoDB • Dati replicati in minuti • Sviluppo più rapido • Sposta i Capex a Opex Tier 1 Bank $40m Savings
    23. 23. 80% di costi in meno • Prodotti di foto digitali personalizzati – Sviluppato su Oracle, non scalabile • Perché MongoDB – Modello dei dati ricco che supporta nuovi pattern di query – Nuove features sviluppate in settimane e non in mesi – MMS per monitoring e risolvere i problemi • Risultati – Performance 9 volte migliori con codice semplificato – Riduzione costi dell’80%
    24. 24. Raggiungere il successo più velocemente
    25. 25. MongoDB Enterprise
    26. 26. Automazione (beta) – Installazione in minuti – Upgrade a caldo Backup – Backup continuo incrementale – Point-in-time recovery Monitor – Visualizza oltre 100 metriche – Alert personalizzati MongoDB Management Service
    27. 27. Siamo i Tuoi Partner TRAINING Certificazione & training per sviluppatori e amministratori – online e di persona CONSULENZA Risorse esperte per tutte le fasi di implementazione di MongoDB
    29. 29. Global Community 7,000,000+ MongoDB Downloads 150,000+ Online Education Registrants 35,000+ MongoDB Management Service (MMS) Users 30,000+ MongoDB User Group Members 20,000+ MongoDB DaysAttendees
    30. 30. Un database PUO’ DAVVERO fornire un quantificabile vantaggio competitivo.
    31. 31. Learn More: Download the Whitepaper
    32. 32. For More Information Resource Location Download di MongoDB Training Online Gratuito Webinar e Event White Paper Referenze Presentazioni Documentazione Informazioni aggiuntive Risorsa Indirizzo
    33. 33. Migrated product catalog from RDBMS “Quite frankly we were blown away by the performance of MongoDB. Between the move to Amazon and by opting for MongoDB, we’ve saved about £2m over the last three years” Neil Jennings, LeadArchitect, Commodity Economics
    34. 34. Demand for new types of application Adapt to handle rapidly changing, multi-structured data
    35. 35. Unlock value from new data Process and analyze multi-structured data in real-time
    36. 36. More data than ever before Seamlessly scale database capacity & performance
    37. 37. Smaller windows of market opportunity Enable agile development methodologies
    38. 38. New architectures increase flexibility, decrease cost Ride the economies of commodity & cloud computing Maintain strict enterprise SLAs