January 2022 Summaries

The MongoDB Atlas Hackathon was announced in December 2021, with a judging panel impressed by over 210 submissions. The submissions were categorized into five categories: Action Star, Automation Innovation, E-commerce Creation, Prime Time, and Choose Your Own Adventure. Winners were selected for their projects, including Souvik's Plant Monitor that used MongoDB Realm Functions and Triggers to track plant health, Alex's New Year Resolution Tracker with Weekly Automated Reports that utilized a MongoDB Atlas Serverless instance, and Patrick's Groovemade e-commerce app using MongoDB Atlas Search. Additionally, Kai's Temperature Sensing with Raspberry Pi into MongoDB project stood out in the Prime Time category, while Valeria's Asteria: Asteroids approaching Earth today project won the Choose Your Own Adventure category. The jury also picked ten runner-up projects for prizes worth $250 each.

MongoDB's Technical Services team provides 24/7 support to customers, addressing complex technical challenges and ensuring their MongoDB deployments run at optimal performance. The team is distributed globally, comprising experts in various fields, who collaborate on internal projects such as developing support tools for performance tuning, benchmarking, and diagnostics. Three team members share their career journeys, highlighting the importance of collaboration, continuous learning, and adapting to new technologies. As Staff Engineers, they work closely with customers, contribute to project development, and participate in leadership initiatives, fostering a culture of expertise sharing and growth within the Technical Services team. The team's diverse backgrounds and experiences enable them to address unique issues and provide holistic support, making MongoDB a compelling choice for those interested in a career in Technical Services.

Is Relational the New COBOL? What the History of Technology Tells Us About Change` explores how technology evolves and what causes one technology to become dominant while another fades away. The article discusses the history of COBOL, a programming language that was once widely used but is now largely obsolete. Similarly, relational databases are still in use for legacy applications but are no longer relevant for innovation due to their inefficiencies and limitations. According to MongoDB CTO Mark Porter, developers are not interested in working with relational databases because they are not scalable or flexible enough to support new applications. Instead, modern data platforms offer enterprise-grade scalability, flexibility, and intuitiveness. As companies focus on differentiating themselves through innovation during the pandemic, those relying on relational databases are at a disadvantage when it comes to scaling and keeping pace with competitors.

The blog post addresses several myths about MongoDB, highlighting misconceptions about its capabilities and features. It clarifies that MongoDB, a distributed document database, supports relationships, transactions, and ACID properties, contrary to outdated beliefs. The post explains MongoDB's use of BSON rather than JSON, emphasizing its efficiency and support for a wider range of data types. It also discusses MongoDB's sharding feature, which is beneficial for handling large data sets but requires careful consideration of hardware upgrades as alternatives. The post touches on MongoDB's security, noting past issues with insecure instances due to default settings, which have since been rectified. Additionally, the author shares personal experiences and professional growth within MongoDB, underscoring the company’s supportive environment and the collaborative nature of the Technical Services team. Finally, it mentions an upcoming leadership transition at MongoDB, with Dev Ittycheria stepping down as CEO and Chirantan "CJ" Desai taking over, highlighting CJ's qualifications and vision for the company's future.

Bliinx is a lead prioritization platform designed to help sales teams identify the best leads and accounts at the right time. The company aims to simplify the process of building relationships with potential customers, especially in the B2B SaaS industry. By analyzing data from various sources such as sales conversations, marketing engagement, and product usage, Bliinx provides sales reps with actionable insights to focus on high-quality leads and nurture revenue growth. The platform connects with popular tools like email, calendar, LinkedIn, Slack, Segment, Intercom, Stripe, Snowflake, and Twitter, allowing for seamless integration and data-driven decision-making. With a strong focus on simplicity, scalability, and human connection, Bliinx is poised to revolutionize the way software is sold by making sales more efficient and effective.

Live resharding is a feature introduced in MongoDB 5.0 that allows users to change the shard key for their collection on demand without any database downtime or complex data migrations. This feature eliminates the need for manual and complex resharding processes, making it easier for developers to scale out their applications horizontally while maintaining data locality and enforcing regulatory compliance. With live resharding, users can review their sharding strategy, change between range, hash, and zones, and even rehome documents to different geographic regions or age data out to slower storage tiers. The process is automated, resilient, and non-disruptive to the application, allowing developers to evolve with their apps in simplicity and resilience. Users should ensure they have sufficient storage capacity available, monitor the resharding progress, and block writes early if necessary to force completion of the resharding operation. Live resharding is available in MongoDB's fully managed Atlas data platform, Enterprise Advanced, and Community Edition, providing a huge step forward in the state of distributed systems and paving the way for future improvements in sharding flexibility and automation.

MongoDB Realm's Flexible Sync is now available in preview, offering a more flexible sync experience that enables complex use cases without requiring custom code. This new iteration allows users to define data synced to user applications using language-native queries, supporting dynamic and overlapping queries based on user inputs. It also introduces document-level permissions, making it easier to limit access to specific documents based on a user's role. Additionally, Flexible Sync optimizes for real-time collaboration by treating single objects or documents as the smallest entity for synchronization, enhancing query performance and conflict resolution. The service is compatible with MongoDB 5.0 and is available now, with plans for future enhancements and integrations.

Faster Migrations to MongoDB Atlas on Google Cloud with migVisor by EPAM` is a partnership between Google Cloud, MongoDB, and EPAM Systems that aims to simplify database migrations to the cloud. EPAM's migration assessment tool, `migVisor`, analyzes database workloads, configuration, and structure to generate a visual cloud migration roadmap, identifying potential quick wins and challenge areas. The tool automates the discovery and assessment process, reducing development cycles from weeks to days, and provides a secure assessment of source and target databases independent of deployed environments. With `migVisor`, customers can better plan migrations, reduce risk, identify quick wins for cost reduction, review migration complexities, and plan migration phases for optimal outcomes, all while leveraging the benefits of MongoDB Atlas on Google Cloud.

MongoDB highlights the challenges of complex database architectures, which can hinder innovation and development speed, and introduces the concept of DIRT (Data and Innovation Recurring Tax) to describe the inefficiencies caused by such complexity. To address these issues, MongoDB, in collaboration with EPAM Systems, offers migVisor, a tool that facilitates cloud database migrations by providing automated assessments and migration roadmaps. Additionally, MongoDB showcases its advancements in AI and data management, including the release of the Voyage 4 model family for enhanced AI capabilities, the introduction of Automated Embedding for semantic searches, and the launch of intelligent assistance within MongoDB Compass and Atlas Data Explorer. These innovations aim to streamline database operations, reduce operational overhead, and enable developers to focus on building unique AI applications without the burden of managing complex infrastructure, thus reinforcing MongoDB's position as a modern data platform designed for scalability and reliability.

As a Solutions Architect in MongoDB's Remote Presales Centre, one is essentially an "incubation" period to gain experience in a presales role and exposure to sales cycles. The team is global, covering various regions and Sales teams, and works with customers across different industries and company sizes. The role involves uncovering the answers to "What is motivating the customer to do this?" and providing clarity on MongoDB technology. A typical week includes one-on-one sessions, webinars, security questionnaires, discovery meetings, and prep calls. To succeed in this role, one needs a mindset shift from focusing on solving specific issues to understanding what drives customers' business directions. The team works with various teams, including Marketing, Sales, Product Owners, Professional Services, and Information Security. The learning curve involves technology learning, sales cycle knowledge, and customer persona understanding. The Remote Presales Centre team offers opportunities for growth, mentorship, and internal visibility, making it an exciting opportunity for those interested in the intersection of business and technology.

MongoDB 5.2 introduces several improvements, including columnar compression for time series collections, which can reduce storage footprint by up to 70%, and enhanced query ergonomics with new operators such as $top, $bottom, $maxN, $minN, and $sortArray, allowing for more efficient queries and reduced code maintenance. The release also includes long-running snapshot queries, improved resilience with faster initial sync via file copy, and an enhanced developer experience with the MongoDB Analyzer for .NET, which enables easier troubleshooting and debugging of MongoDB queries and aggregations.

The digital transformation in Industrial IoT (IIoT) is driven by the need to collect, store, and analyze massive amounts of data generated by thousands of sensors and devices in manufacturing processes. This requires a flexible, scalable, and highly available data platform to support real-time analytics, automation, and decision-making. MongoDB's general-purpose data platform allows manufacturers to store OT/time-series data sets with recipes or digital twins for a complete real-time end-to-end picture from edge to cloud and onto mobile devices. The Industry Solutions team at MongoDB demonstrated how easily IIoT use cases can be built on top of MongoDB's data platform to enable and accelerate the digitalization of manufacturing processes in any industry. By leveraging MongoDB Atlas, Realm, and IoT technologies, manufacturers can reduce complexity, increase developer efficiency, and scale elastically with demand, providing a resilient multi-functional data platform for their IIoT needs.

MongoDB Atlas is a distributed database-as-a-service that offers unparalleled developer experience, horizontal scalability, and flexibility. It provides services like Atlas Search and MongoDB Realm to support modern applications. The platform extends the core database with features such as sub-second queries, automatic indexing, and edge-to-cloud sync. MongoDB Atlas is ideal for storing structured, semi-structured, and unstructured content in a single platform. The platform can be integrated with Google Cloud services, allowing customers to take advantage of cloud-native solutions, automated billing, and region-spanning clusters. HCL Technologies supports customers looking to migrate to MongoDB Atlas on Google Cloud by providing technical expertise in machine learning, data science, and cloud infrastructure. The partnership enables customers to build secure, performant, and cost-effective solutions for transactional, operational, and analytical workloads.

Retail tech is expected to play a crucial role in 2022 as retailers adapt to the "new normal" post-pandemic. Omnichannel shopping will continue to be a key aspect, with retailers needing to invest in solutions that offer a single view of the consumer to personalize offerings and improve customer loyalty. Retailers are also expected to adopt leaner tech stacks by adopting modern data applications that simplify data collection and include automated conflict resolution. Additionally, digital worker enablement is becoming increasingly important to combat worker fatigue and retain employees, with mobile workforce enablement apps being a key area of investment. Finally, retailers will need to invest heavily in the supply chain to mitigate disruptions and prepare for future challenges.

Ventana Research has published an Analyst Perspective on MongoDB, highlighting its role as a cloud data platform provider. The report notes that MongoDB's non-relational database is gaining popularity due to the shift towards modern, cloud-based platforms. Cloud-based services are also becoming increasingly popular, with businesses relying on flexibility and availability of cloud-native data platforms to build competitive products and deliver personalized experiences. As applications become more advanced, operational database requirements will only become more demanding, making a comprehensive platform like MongoDB Atlas essential for success. Convergence is driving innovation, with non-relational databases adding relational features and relational databases offering compatibility for non-relational data models. Companies are increasingly opting for hybrid and multi-cloud models, leveraging exclusive provider features to improve availability and migrate data across clouds without downtime. Non-relational, cloud-native databases are becoming more powerful and attractive to customers, thanks to convergence and competition, offering real-time analytics, rich visualizations, and mobile data sync and storage.

The concept of Safe Software Deployment emphasizes the inherent differences between staging and production environments, which cannot be exactly replicated due to various variables such as hardware, software, configuration, network topology, and patches. Developers should accept reality, approach testing like an actuary, treat both environments like cattle, not pets, and prioritize automated rollbacks to reduce risk and foster confidence. A common understanding of the problem from top-down is crucial for implementing a system of best practices that greatly reduces risk and fosters confidence in deploying software from staging to production.

TM Forum Open APIs have been adopted by many of the world's largest communication service providers (CSPs) and software provider ecosystem, with MongoDB playing a significant role in their implementation. The use of TMF Open APIs allows CSPs to adopt a modular architecture made up of best-of-breed components while minimizing integration time and cost. The MongoDB document model enables developers to work with data naturally and store it as it is retrieved by the application, persisting TMF resources 1:1 in the database without additional mappings. This flexibility allows CSPs to achieve agility and innovate at the same time, enabling them to build new microservices in days instead of weeks or months. With MongoDB's support for full-stack digital BSS and flexible querying capabilities, CSPs can rapidly develop TMF-compliant microservices and query data flexibly using TMF specifications. Additionally, MongoDB's distributed transaction capabilities provide a database-level solution for business processes such as customer creation, reducing the need for atomic transactions in relational databases.