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.
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
