MongoDB Partner of the Year Award Winners 2021

Alan Chhabra
July 14, 2021
#Partners

The last 12 months have been a remarkably challenging time, with widespread changes affecting the entire world—and certainly the IT industry—like never before. However, the pandemic has also brought customers and partners further together to solve common problems, and in particular, one major trend we’ve seen accelerated is the move toward cloud modernization. At MongoDB, we’re committed to help our customers evolve to this next stage of necessary innovation and are so grateful to our 1000+ Partners who help make it happen.

A handful of strategic partners went above and beyond and I would like to congratulate Featurespace, Zaloni, Carahsoft, TCS, PeerIslands, Alibaba, AWS, and Google Cloud as our Partners of the Year! I’m excited to have shared this year’s winners during my Partner Keynote at MongoDB.live. You can still head to MongoDB.live to watch it on demand.

Independent Software Vendor (ISV) Partner of the Year

Feature Space is a disruptive company in the security space and the inventor of Adaptive Behavioral Analytics and Automated Deep Behavioral Networks technology for fraud and financial crime management. Trusted by the world’s largest banks, insurance companies and gaming organizations, Feature Space embeds MongoDB as their database platform, for both on-premise and SaaS deployment offerings. Learn more about the partnership here.

Technology Partner of the Year

Zaloni is a MongoDB data supply chain and modernization partner that helps its customers catalogue and transform their data to enhance analytics and real-time applications. A recent engagement with a fleet management client required Zaloni to move and modernize four billion records of data built on SQL to new microservices in the cloud. Using MongoDB Atlas, Zaloni helped their client successfully scale and reach new levels of customer satisfaction. Learn more about the partnership here.

Reseller Partner of the Year

Carahsoft is a trusted, long-standing partner and they continue to be one of MongoDB’s largest resellers in the world. Carahsoft’s depth and reach in the Public Sector market helps government agencies leverage Open Source technologies to drive innovation, maximize cost efficiencies and achieve success for their digital modernization initiatives. They’ve been critical to growing MongoDB’s agency, civilian and DOD business and we’re excited for what’s next. Learn more about the partnership here.

Global System Integrator Partner of the Year

Tata Consultancy Services, a leading multinational IT services and consulting company, leverages its IP-based solutions to accelerate and optimize service delivery. TCS MasterCraft™ TransformPlus uses intelligent automation to modernize and migrate enterprise-level mainframe applications to MongoDB’s leading-edge architecture and database. Together, TCS and MongoDB simplify and accelerate the customer journey to the cloud. Learn more about the partnership here.

Boutique System Integrator Partner of the Year

PeerIslands is a boutique consultancy focused on helping clients accelerate product development with cloud-based solutions. An invaluable MongoDB partner with expertise in ecommerce and inventory management modernization, PeerIslands has helped MongoDB’s ISV and retail customers modernize, moving software built for on-prem to SaaS environments more conducive to cloud environments. Learn more about the partnership here.

Cloud (Emerging) Partner of the Year

Alibaba Cloud is one of MongoDB’s largest Cloud OEM partners in the world. In our second year of our partnership with Alibaba Cloud as an authorized MongoDB-as-a-service solution, MongoDB has seen some of our strongest adoption numbers yet in mainland China. With this partnership, Alibaba Cloud ensures end-to-end management and support for customers on current and future versions of MongoDB, with the ability to escalate bug fixes and support issues on their behalf. Users of Alibaba Cloud’s platform offering receive easy access to the latest MongoDB features and capabilities, backed by comprehensive support from Alibaba Cloud and MongoDB, and we remain thrilled to scale this partnership. Learn more about the partnership here.

Cloud (Co-Sell) Partner of the Year

AWS provides a massive global cloud infrastructure that allows customers to rapidly innovate and iterate. Over the past year, MongoDB and AWS sellers came together to help customers modernize, accelerate consumption of EDPs, and close on major cross-industry and cross-vertical deals around the world. We’ve partnered together to help customers build modern, event-driven serverless applications. And as recently as April 2021, we launched a new AWS Quick Start for MongoDB Atlas, which allows AWS customers to quickly and easily launch a basic MongoDB Atlas deployment from the AWS CLI or console, taking advantage of AWS CloudFormation’s seamless automation. We also released integrations for Atlas with Amazon EventBridge, Amazon Kinesis, AWS App Runner, AWS PrivateLink, AWS Wavelength, and more in the last year. With additional integrations in the pipeline, we know there’s so much more to come with our partnership. Learn more about AWS and MongoDB here.

Cloud (Marketplace) Partner of the Year

Google Cloud views the database as an essential building block of cloud infrastructure. Since launching MongoDB Atlas on Google Cloud Marketplace over the past two years, our partnership has seen rapid adoption and acceleration across industries such as gaming, retail, healthcare, financial services, and automotive. In the last 12 months, we have integrated Atlas with more Google services, including DataStream, BigQuery, DataFlow, Cloud Run, App Engine, and Cloud Functions, helping our joint customers innovate faster. Additionally, Google Cloud’s mainframe modernization solutions now support MongoDB Atlas and help customers convert legacy COBOL code on mainframes into modern Java-based applications built on MongoDB. Together, G4 and MongoDB Atlas accelerate the modernization and migration process for organizations moving their business-critical workloads to the cloud. More and more of Google Cloud’s customers are choosing to run MongoDB Atlas for a variety of needs, such as managing large-scale product catalogs of popular e-commerce websites, building great customer experiences by unifying disparate pieces of data, or building modern global web and mobile applications. Learn more about the partnership here.

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Fine-Tune Relevance in MongoDB Atlas Search with Function Scoring and Synonyms

MongoDB Atlas Search is an embedded full-text search solution in MongoDB Atlas that gives developers a seamless and scalable experience for building fast, relevance-based application features. We announced its general availability last year at MongoDB.live 2020 and over the past year we’ve introduced many new features, including a visual index builder, search query tester, custom analyzers , and wildcard path queries . This year at MongoDB.live 2021 , we’re excited to highlight two new capabilities that help developers tune the relevance of search results. See how easy it is to get started with MongoDB Atlas Search in this demo video by Marcus Eagan, Senior Product Manager for Atlas Search. Building relevance into search results Understanding the behavior of your users is essential when thinking about search result relevance. People don’t always tell you what they want, and they sometimes use words or phrases that don’t match your content exactly. To cover these scenarios, you can use full-text search features like function scoring and synonyms. Influence search rankings with function scoring There are often multiple factors that influence how search results should be ranked. For example, let’s say you have a restaurant finder application. The explicit inputs are things like the user’s location and what they’re searching for, but what’s implied is that they likely want to see highly rated restaurants or ones with more reviews. What’s Cooking: a sample restaurant finder application using MongoDB Atlas Search Function scoring allows you to influence the order of results returned by manipulating the score of each result. In Atlas Search, that means you can use a numeric field in a document and apply a mathematical expression to it. For example, you might want to increase the score of restaurants that are sponsored or have higher star ratings. This can easily be accomplished within the same search query by simply adding the function option to the score parameter of your query. Learn more about how to use function scores in our developer tutorial . Show results for more search queries with synonyms Synonyms are often used to define terms that are semantically similar to each other to improve search results. For example, someone searching for “noodles” might want to find results for “spaghetti”, “chow mein”, or “pad thai”. Synonyms can also help with typos, especially on mobile and small keyboards. In Atlas Search, you can define collections of synonyms for a search index via the API. Synonyms can be explicit (one-way) or equivalent (two-way). Explicit synonyms are good for defining relationships between terms that are subsets of each other, like the noodle example above: “spaghetti”, “chow mein”, and “pad thai” are all explicit synonyms for “noodles”, but not each other (you don’t want results for “chow mein” in a search for “spaghetti”). Equivalent synonyms are often used for terms that have regional variations or are otherwise interchangeable both ways, like soda and pop, or Kleenex and tissues. What's next for Atlas Search Developers are increasingly turning to full-text search to make content more discoverable and relevant for application end users. With Atlas Search, we hope to not only make building full-text search easier, but also more powerful and expressive. Join our community to ask questions and find out what other developers are building with Atlas Search and let us know what you think we should build next in our feedback forums .

July 13, 2021

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MongoDB: Powering Digital Natives

Today's rapidly evolving digital landscape is dominated by digital native companies, driving innovation . These are companies born in the digital age and who operate through digital channels with a business model enabled by technology and data. They are not only adept at using technology but are also reshaping the way software is developed and deployed. This article delves into the challenges and opportunities facing digital natives in modern application development, with a particular focus on the complexities of managing data. We’ll explore how the right data platform can empower your digital native organization to build high-quality software faster, adapt to changing market demands, and unlock the full potential of your business. Strong foundations: The four pillars of tech-fueled growth for digital natives Achieving explosive growth requires a strong foundation built on specific principles, which empower rapid scaling and success. Here, we explore the four key pillars that fuel tech-driven growth for digital natives: Product-market fit, fast: As a digital native, you must continuously ship and iterate products to achieve a quick product-market fit. This builds customer trust and captures opportunities before competitors can in an evolving market. Data and AI-driven decisions: You must leverage data to personalize experiences, automate processes, and guide product decisions. A robust data architecture feeds real-time data into AI models, enabling data-driven decisions organization-wide. Balance of freedom and control: Your developers must have the freedom to choose technologies, even as your organization maintains control over the infrastructure to manage risks and costs at scale. Selected technologies must integrate within your overall technology estate. Extensible and open technologies: You must explore disruptive technologies while maintaining existing systems. Freedom from platform and vendor lock-in enables quick adoption of innovations, from current generative AI capabilities to future technological advances. Data: The unsolved challenge in modern application development From cloud platforms and managed services to gen AI code assistants, advancements have transformed how engineering teams build, ship, and run applications: Agile methods and programmatic APIs streamline development, while CI/CD and infrastructure as code automate processes. Containerization, microservices, and serverless architectures enable modularity, while new languages and frameworks boost capabilities. Enhanced logging and monitoring tools provide deep application health insights. Figure 1: Tools and processes to maximize velocity. But none of these advancements address where developers spend most of their time— data . In fact, 73% of developers share time and again that working with data is the hardest part of building an application or feature. So why is data the problem? Traditionally, selecting a database, often an open-source relational one, is the first step in development. However, these databases can struggle with the characteristics of modern data: it’s high volume, unstructured, and constantly evolving. As applications mature and their data demands grow, development teams may encounter challenges with achieving scalability and maintaining service resilience. Some teams turn to NoSQL databases, but even then they find there are limited capabilities, pushing them back to relational databases. As the application gains traction, the business’s appetite for innovation grows, compelling development teams to incorporate an expanding array of database technologies. This results in an architectural sprawl, imposing on teams the challenges of mastering, sustaining, and harmonizing new technologies. Concurrently, the dynamic technology landscape undergoes constant evolution, demanding teams to swiftly adjust. As a result, self-contained, autonomous teams encounter these hurdles recurrently, highlighting the pressing need for streamlined solutions to mitigate complexity and enhance agility. Figure 2: The evolving tech landscape. Data sprawl: A major threat to developer productivity and business agility Data sprawl is slowing everyone down. The more systems we add, the harder it is for developers to keep up. Each new database brings its own unique language, format, and way of working. This creates a huge headache for managing everything—from buying new systems to making sure they all work together securely. It’s a constant battle to keep data accessible, consistent, and backed up across all these different platforms. Figure 3: Teams building on separate stacks leads to data sprawl and manageability issues across the organization It compromises every single one of the four outcomes your technology foundation should be providing, yielding the opposite results: Missed opportunities, lost customers: Fragmented development experiences consume time as engineers struggle with multiple technologies, frameworks, and extract, transform, and load mechanisms for duplicating data between systems. This slows down releases, degrades digital product quality, and impedes engineers from achieving product-market fit and effective competition. Flying blind: With your operational data siloed across multiple systems, you lack the data foundations necessary to use live data in shaping customer experiences or reacting to market changes. This is because you are unable to feed reliable, consistent, real-time data into your AI models to take action within the flow of the application or to provide the business with up-to-the-second visibility into operations. High attrition, high costs: Complex data architecture impacts development team culture, leading to siloed knowledge, inefficient collaboration, and decreased developer satisfaction. This complexity also consumes substantial resources in maintaining existing systems by diverting resources from new projects that are vital for business competition in new markets. Disruption from new technologies: Dependence on any one cloud provider can stifle innovation for development teams by restricting access to the latest technologies. Developers are confined to the tools and services offered by a single provider, hindering their ability to explore and integrate new, potentially more efficient, or advanced technologies. Speed: A unified developer experience for building high-quality software faster In today’s digital world, speed is king. Your customers expect seamless experiences, but clunky applications leave them frustrated. But traditional databases can be a bottleneck, struggling to keep pace with your ever-evolving data and slowing down development. The future of data is here, and it’s flexible: a data platform built for digital natives . It leverages a flexible document model, letting you store and work with your data exactly how you need it. This eliminates rigid structures and complex migrations, freeing your developers to focus on what matters—building amazing applications faster. Flexible document data models empower developers to handle today’s rapidly evolving application data ( 80%+ unstructured) that relational databases struggle with. MongoDB documents are richly typed, boosting developer productivity by eliminating the need for lengthy schema migrations when implementing new features. Developers get to use their preferred tools and languages. Through its drivers and integrations, MongoDB supports all of the most popular programming languages, frameworks, integrated development environments, and AI-code assistance tools. MongoDB scales! It starts small and scales globally. Built for elasticity and horizontal scaling, it handles massive workloads without app changes. Figure 4: A unified developer experience, integrating all necessary data services for building sophisticated modern applications Introducing MongoDB Atlas : a fully-managed cloud database built for the modern developer. It enables the integration of real-time data from devices with AI capabilities (through vector embeddings and large language models ) to personalize user experiences. Stream processing empowers constant data analysis, while in-app analytics provides real-time insights without needing separate data warehouses, all while automatically managing data movement and storage for cost-effectiveness. MongoDB Atlas simplifies database management with the following: Easy deployment via UI, API, CLI, Kubernetes, and infrastructure as code tools. Automated operations for cost-effective performance and real-time monitoring. MongoDB Atlas customer success stories: Development with speed, scale, and efficiency Delivery Hero Delivery Hero, a global leader in online food delivery, leverages MongoDB Atlas to power its rapid service. Founded in 2011, Delivery Hero now serves millions of customers in over 70 countries through brands like PedidosYa, foodpanda, and Glovo. Having replaced its legacy SQL database, Delivery Hero optimized operations and bolstered performance by using MongoDB Atlas. By leveraging MongoDB Atlas Search, Delivery Hero revolutionized its search functionality, ensuring a seamless user experience for its extensive customer base through simplified indexing and real-time data accuracy. MongoDB’s scalability has empowered Delivery Hero to manage over 100 million products in its catalog without encountering latency issues, enabling the company to expand its services while maintaining peak performance. This agility, coupled with MongoDB’s cost-effectiveness, has enabled Delivery Hero to swiftly adapt to evolving customer demands, solidifying its position in the fiercely competitive delivery market. MongoDB Atlas Search was a game changer. We ran a proof of concept and discovered how easy it is to use. We can index in one click, and because it’s a feature of MongoDB, we know data is always up-to-date and accurate. Andrii Hrachov, Principal Software Engineer, Delivery Hero Read the full customer story to learn more. Coinbase Coinbase, a prominent cryptocurrency exchange boasting 245,000 ecosystem partners and managing assets worth $273 billion , trusts MongoDB to handle its extensive data workload. As the company grew, MongoDB scaled seamlessly to accommodate the increased demand. To further improve performance in the fast-paced crypto world, Coinbase partnered with MongoDB to develop a system that significantly accelerated data transfer to reporting tools, reducing processing time from days to a mere 5-6 hours. This near real-time data access enables Coinbase to rapidly analyze trends and make informed decisions, maintaining a competitive edge in the ever-evolving crypto landscape. Watch Coinbase's full session at MongoDB.local Austin, 2024 to learn more. MongoDB: Your flexible platform for digital growth With MongoDB, you can freely explore, experiment, develop, and deploy according to your digital-native business needs. If you would like to learn more about how MongoDB can empower your digital-native business to conquer market trends, visit: Innovate With AI: The Future Enterprise Application-Driven Intelligence: Defining the Next Wave of Modern Apps AI-Driven Real-Time Pricing with MongoDB and Vertex AI

November 7, 2024