November 2022 Summaries

Choosing the Right Tool for the Job: Understanding the Analytics Spectrum` discusses the need for application-driven analytics in today's digital economy where organizations want to create competitive advantage, reduce costs and risk, and increase efficiency by enabling faster decisions on fresher data. This approach complements traditional centralized analytics systems, which are designed to process large datasets but may not be suitable for real-time applications. The spectrum of capabilities required for application-driven analytics includes continuous querying of operational system data with low latency, working with smaller subsets of data, and running less complex queries compared to centralized analytics. By choosing the right tool for the job, organizations can maximize competitive advantage through smarter applications, improve customer experience and loyalty, reduce costs, and out-innovate their competitors.

Inspirit is a Palo Alto-based startup that has developed an immersive, interactive VR platform to help students learn science and math through virtual reality. The company uses MongoDB as its database, which provides flexibility and support for the startup's growth and scaling. Inspirit aims to make learning more engaging and accessible for students, particularly those who struggle with STEM subjects. By providing interactive 3D models and simulations, Inspirit helps teachers equip their students with the tools they need to succeed in science and math. The company has evolved since its early days, pivoting to a web platform during the pandemic, and now offers a cross-platform solution to make learning more accessible.

A headless architecture is a decoupled approach where the layers or components of an application are separated, with the "heads" (frontends) operating independently from the backend logic or "core body" microservices and sharing data via API. Retail was one of the first industries to adopt this concept in 2012, focusing on building modern ecommerce solutions that can meet rapidly changing customer requirements and stand out from competitors. This approach enables companies to bring new features to market faster, scale to meet seasonal demand, and leverage best-of-breed technologies while avoiding vendor lock-in and improving talent acquisition and retention. A headless architecture also makes it easier to pinpoint issues and reduce downtime, as well as removing data silos and sharing data across multiple journeys. MongoDB is a strong fit for this approach due to its flexible document model, API capabilities, sharding capabilities, and high availability, allowing developers to deliver faster with no downtime, scale effortlessly, support composable architectures, and provide a seamless experience to customers.

MongoDB has collaborated with Amazon Web Services (AWS) for nearly a decade, but in 2022, their partnership saw significant growth and a strategic collaboration agreement. The two companies have worked together on joint product engineering and integration, making MongoDB Atlas a first-party service on AWS. This collaboration has resulted in dramatic growth in the quantity and quality of their joint activities, with MongoDB Atlas becoming one of the most popular self-service listings on the AWS Marketplace, featuring over 1,000 customers. The partnership has also led to increased customer adoption, particularly in Europe, with AWS naming MongoDB their AWS Marketplace Partner of the Year - EMEA in November 2022. To simplify the purchasing experience for customers, MongoDB and AWS have made it easier to procure MongoDB Atlas on AWS by using a standard contract and security assessments. The companies have also improved product integrations, including tight integration with AWS services such as Amazon EC2, S3, and container services like Amazon EKS. Additionally, they have strengthened integrations with joint partners like Datadog, Databricks, and Confluent, making it easier for customers to use MongoDB with these partners. The partnership has helped make thousands of customers successful running MongoDB on AWS, with some using the technology to upend entire industries.

Three key characteristics of modernization are modernization capabilities, modernization outcomes, and a modernization platform. Modernization capabilities include enabling better data management for data science, AI, and ML, supporting development and deployment of data-driven applications, self-service Business Intelligence (BI) and analytics users, unifying management of data across distributed systems, handling an increase in data volume and the number of concurrent users, reducing data latency and increasing the frequency of updates. Modernization outcomes include gaining fuller value from the data stored and captured, automating decision-making, increasing efficiency and effectiveness, generating new business strategies and models using analytics, making faster decisions, strengthening relationships via data sharing, improving trust and data quality, increasing reuse and flexibility, reducing costs, providing authorized access to live data sets, consolidating data silos. A modernization platform is the key solution that solves the issues of consolidating unnecessary data silos and ensuring access to data without manual intervention or unauthorized access, with advantages including simplifying and accelerating access, discovering data relationships easier and faster, creating a logical layer for single point of access, unifying data governance, reducing unnecessary data movement. Modernized architecture often includes cloud migration from on-premises systems, hybrid multi-cloud architectures, distributed architectures, serverless architecture.

MongoDB has been a key partner of AWS since its inception in 2012, with the company attending re:Invent annually to engage with its joint customers and showcase their success stories. Over the years, several MongoDB customers have been featured in re:Invent keynotes, including Capital One, Goldman Sachs, Citi, Barclays, BBVA, Charles Schwab, FICO, HSBC, and Intuit. These companies use MongoDB to power their financial services, scientific research, and data-driven applications. Additionally, notable customers such as NASA, Verizon, Epic Games, Volkswagen, and Siemens have also adopted MongoDB to support their cloud-first strategies. The partnership between MongoDB and AWS has enabled these customers to leverage the agility and performance of both technologies, driving innovation and growth in various industries.

Modern GraphQL APIs are essential for modern applications that require data from multiple sources, which are often backed by different databases and fronted by various REST APIs. GraphQL provides a complete description of the data in an API, allowing clients to ask for exactly what they need while making it easier to evolve APIs over time. MongoDB Atlas is a modern developer data platform with a fully managed cloud database that complements popular development stacks like MEAN and MERN, aggregating data from multiple origins into a single source. AWS AppSync allows developers to build GraphQL and Pub/Sub APIs, enabling real-time interactions in applications and providing serverless scalability. By integrating MongoDB Atlas and AWS AppSync, developers can create scalable GraphQL APIs by consolidating multiple REST APIs and data sources on AWS, offering flexibility in defining the structure of the data while reducing payload size. The solution involves using Lambda Resolvers to translate GraphQL requests and retrieve data from MongoDB Atlas, with options to use the Atlas Data API or connect directly via MongoDB drivers.

MongoDB has partnered with Auth0 to help startups combat security risks, providing a secure data platform in MongoDB and secure access through Auth0. The programs are designed to support high-growth startups from ideation to IPO, offering credits for MongoDB cloud products, technical advisors, co-marketing opportunities, and access to the developer ecosystem. Both programs aim to enable startups to focus on growing their business quickly while managing responsibly their data.

MongoDB and AWS are collaborating to simplify metadata management for the Open Subsurface Data Universe (OSDU), a new data platform standard for the energy industry, by leveraging MongoDB's flexibility and scalability. OSDU aims to reduce data silos and enable transformational workflows through an open, standards-based API set and supporting ecosystem. With this collaboration, MongoDB provides a robust multi-region OSDU offering, allowing customers to adapt to varying deployment scenarios, from on-premises to cloud, while supporting the unique challenges of OSDU metadata management. The document model of MongoDB offers flexibility in handling metadata, enabling users to model and query data in various ways without proliferating disparate databases, which incurs overhead in terms of deployment, cost, scale, and querying. Additionally, MongoDB's scalability and support for cross-regional data replication enable seamless deployment across multiple regions, including on-premises, private cloud, public cloud, and SaaS implementations.

MongoDB offers a flexible and secure way to manage and store data where organizations want it, whether on-premises, in the cloud, or as a globally distributed database. To meet their data goals, companies must consider factors such as process, penalties, scalability, infrastructure, flexibility, and cost when using MongoDB. The platform provides features like sharding, network isolation, multi-cloud clusters, IP whitelists, queryable encryption, and client-side field level encryption to support organizations in storing and managing data securely and efficiently. Additionally, MongoDB Atlas offers intuitive UIs for administration tasks, scalability with a few clicks, and meeting data goals with its range of features.

MongoDB has enhanced its Performance Advisor tool, now available in MongoDB Atlas, Cloud Manager, and Ops Manager. The updated tool provides a new ranking algorithm, additional performance statistics, support for more query types, and more deterministic index recommendations. This allows users to better understand the impact of each index recommendation and make data-driven decisions to optimize their database's performance. With Performance Advisor, MongoDB aims to simplify database monitoring and provide a cost-efficient way to ensure optimal performance. The tool is available on M10 cluster tiers and higher in MongoDB Atlas, Cloud Manager, and Ops Manager.

MongoDB and Databricks have formed a powerful partnership to operationalize AI-enhanced real-time applications, making it easier for enterprises to unify their data, analytics, and AI. By integrating MongoDB Atlas with the Databricks Lakehouse Platform, developers and analytics teams can collaborate more closely on building intelligent applications that deliver real-time analytics and handle complex data warehouse/BI workloads. This partnership enables application-driven analytics, allowing teams to harness live application data across traditionally separate domains, improving query efficiency and delivering smarter applications in real-time.

To unlock the latent power of application data that exists across the data estate, developers need a powerful API that allows them to query data in various ways and perform CRUD operations, sophisticated aggregations, and data transformations. They also require a versatile query engine and indexing for efficient results, as well as tools to monitor query performance and optimize database queries. To make sense of voluminous streams of time series data, developers need optimized time series collection types, clustered indexes, and mechanisms to automate data lifecycle management. Creating intelligent applications that automatically react to events in real-time requires capabilities such as change streams, triggers, and functions. Combining live application data with aged data for predictions demands the ability to query, blend, and analyze data from various sources, including hot database storage and cooler cloud storage. Finally, bringing analytics into applications without compromising performance necessitates a distributed architecture, sophisticated replication techniques, and a unified platform that manages both transactional and analytical workloads.

Indeed operates enterprise-wide global clusters in the cloud across multiple availability zones worldwide, utilizing MongoDB for approximately 50% of its operations. Running these clusters can introduce performance issues due to initial node syncs, replication lags, and changes in sync sources. To address these challenges, Indeed uses techniques such as overriding sync sources, speeding up replication with WiredTiger cache size adjustments, and monitoring write performance to identify potential problems before they impact users. Additionally, the company configures write concerns across Availability Zones in AWS to ensure seamless data replication and minimize downtime. By adopting proactive strategies, Indeed has improved its overall resilience and performance, enabling faster response times and better end-user experiences.

During MongoDB's Skunkworks week, a project led by Boris Dogadov focused on creating a MongoDB Analyzer for .NET, leveraging the Roslyn API to address the challenges of converting C# LINQ and Builder expressions into MongoDB Query Language (MQL) at compile time. This effort aimed to facilitate query optimization and debugging by generating MQL dynamically without embedding fixed driver dependencies, thus maintaining driver-version agnosticism. Despite the challenges of data type resolution, variable handling, and driver compatibility, the project swiftly led to a functional prototype, thanks to the collaborative environment at MongoDB. The successful prototype paved the way for a rapid development and release of a complete product, supported by a remote team of cross-functional experts. The initiative highlights MongoDB's commitment to innovation and the efficient leveraging of internal hackathons to accelerate product development and community engagement.

MongoDB has launched an enhanced version of its education platform, MongoDB University, which offers a more streamlined and accessible way to learn MongoDB and advance one's career. The new experience includes new courses in various programming languages, discounts and incentives for growth, easier accessibility to course videos, language subtitles, short-form content on newer features, an enhanced certification process with digital badges, updated labs, and the ability to track progress. The platform is designed to support developers as they continue to be a boardroom priority, and provides a seamless path to MongoDB certification, enabling users to take their skills and career to the next level.

Qubitro, a Delaware-based startup, is transforming businesses by making device data accessible anywhere it's needed. The company offers the fastest way of collecting and processing device data to activate it in applications. Qubitro's mission is to make any data published from devices flow over its network, enabling data-driven decision-making and modern application development. The company has partnered with MongoDB Atlas, which provides a platform for building upon, including managed connectivity solutions, user interface, and APIs. By leveraging MongoDB Atlas, Qubitro aims to process massive amounts of IoT data in milliseconds while maintaining privacy and user experience. With the help of the MongoDB for Startups program, Qubitro is able to scale faster and attract more talent, ultimately aiming to become a fabric of digital transformation powered by device data.

MongoDB is exploring the concept of hybrid cloud, which combines public and private cloud infrastructure to provide a flexible architecture for financial services companies. This approach allows institutions to use public cloud for tasks with dynamic resource requirements, such as payments processing, while keeping sensitive workloads on in-house systems. Hybrid cloud offers advantages including reduced capital expenses, improved responsiveness, and enhanced compliance, resilience, and performance. Financial services companies can prepare for a hybrid cloud future by setting clear goals, evaluating customer profiles, profiling assets, blending private and public clouds, building a team with the right skills, fostering transparency, and mapping their migration process. With the right approach, institutions can achieve cost efficiency, flexibility, and competitiveness in the face of rapidly changing customer demands and emerging technologies.

MongoDB Atlas is a solution for companies to migrate to a document-based database, removing the need for complex object-relational mapping layers and allowing developers to build and release new features quicker. The migration process can be streamlined with MongoDB Relational Migrator, which analyzes existing relational schema, designs a new MongoDB schema, and performs data migration. This solution is well integrated into the AWS environment and works seamlessly with various AWS products. Companies like Cox Automotive have successfully migrated their relational workloads to MongoDB Atlas on AWS, leveraging capabilities like Atlas Data Lake and Atlas App Services. However, careful consideration of data modeling is crucial when approaching this challenge, as a naive migration may not deliver the benefits of MongoDB's document-based database. Relational Migrator supports both one-shot and continuous sync migrations, allowing developers to map their relational schema or just a piece of it to a new MongoDB schema.

At MongoDB, customer experience is a core part of their culture and business approach. The company prioritizes understanding its customers' technical and business goals to help them achieve objectives. To put this into practice, MongoDB has implemented several key strategies including a dedicated customer success function, goal-focused onboarding, in-depth success planning, open office hours, and information at your fingertips. These initiatives aim to provide customers with the support and resources they need to get the most out of their investment in MongoDB products. By doing so, MongoDB aims to foster long-term partnerships and drive business outcomes for its customers.

The MongoDB internship program has provided Sahi Muthyala with a valuable learning experience and culture that aligns with her interests and skills. She is interning on the Atlas Growth team, where she is working on product research, collaboration, and connection. The team's cross-functional approach to brainstorming experiments and iterating based on results excites her, as does the company's user-obsessed culture and emphasis on making products that address users' needs. Sahi has grown significantly as a young professional during her internship, learning from her mentor Richa and feeling supported by the Atlas Growth team. She is excited about the impact that MongoDB can have and is eager to contribute to its growth and development in the future.

Here's a neutral and interesting summary of the text: The MongoDB team will be attending AWS re:Invent 2022 in Las Vegas, where they'll showcase their fully managed developer data platform, MongoDB Atlas on AWS, to help developers build applications that are highly available, performant at global scale, and compliant with demanding security standards. The event features over 1,500 workshops, presentations, and demos, and attracts more than 50,000 attendees. The MongoDB booth will include interactive demo kiosks, guided workshops, lightning talk sessions, and after-hours events, such as a pub crawl and disco party. MongoDB experts will also host breakout sessions on topics like the developer data platform, edge computing, and how to build applications with AWS services. Attendees can try out Atlas with AWS today through various channels, including the AWS marketplace, and learn more about upcoming events and resources on the event web page.