As we enter 2024, the pace of digital transformation continues to accelerate across industries. Organizations are increasingly looking to build modern, scalable applications that can adapt to rapidly changing customer demands. This makes choosing the right tech stack a crucial decision.
The tech stack provides the architecture and tools for developing and delivering applications. As new programming languages, frameworks, and infrastructure options emerge, deciding on a future-proof tech stack gets more challenging.
This article looks at the top 5 tech stacks that are expected to drive maximum impact and value in 2024 and beyond:
Let’s Explore Top 5 Tech Stacks in 2024
1. MERN Stack
- MongoDB – Document-oriented NoSQL database that stores data in flexible JSON-like documents
- ExpressJS – Fast and minimalist web framework for Node.js
Some key advantages of the MERN stack are:
- Speed and performance – Node.js and React provide great performance while MongoDBdelivers high throughput database capabilities
- Flexibility – MongoDB’s dynamic schemas and React’s component-based architecture allows quick iteration
- Scalability – All layers designed for horizontal scale to support enterprise workloads
The MERN stack makes it easy to build sleek, high-performance applications with excellent user experience. It suits web/mobile apps with complex, data-driven frontend needs interacting with feature-rich backends. The stack has gained lots of traction and is expected to be hugely popular in 2024.
Practical Example: Building a Social Learning Platform
Let’s see how the MERN stack can be leveraged for a social learning platform like Udemy:
- MongoDB – Store user profiles, course metadata, reviews, Q&A in JSON format. Index text fields for search. Reference user data across documents.
- Express + Node.js – Handle signups, authentication and REST API routes. Server-side business logic.
- React – Render responsive course catalog, video player, forums using reusable components like headers, sidebars.
- Node.js – Power real-time analytics on course engagement stats.
This shows how the MERN stack caters to data-driven, community platforms with React frontends consuming Express + MongoDB backends. The flexibility to evolve schemas and UI fast makes it a great fit.
2. Java + Spring Boot Stack
Key Components: Java, Spring Boot, PostgreSQL/MySQL
For enterprises, Java + Spring Boot will continue to be a dominant application stack, powering business critical systems. It offers:
- Java – Robust, mature, enterprise-grade language
- Spring Boot – Opinionated Java framework making it easy to build standalone, production-grade applications
- SQL Database – PostgreSQL, MySQL providing data integrity protections
Key strengths of this stack are:
- Enterprise capabilities – Transactions, stability required by large organizations
- Rich ecosystem – Huge array of 3rd party libraries for diverse integrations
- Container-friendly – Cloud-native, microservices friendly runtime
- Productivity – Rapid Application Development using SpringBoot templates and scaffolding
Due to these factors, Java + Spring Boot will stay highly relevant in 2024 for developing and delivering enterprise backend services. While typical usage may shift towards containers, orchestration and NoSQL data stores, Java will continue to power mission-critical systems due to its maturity and many advanced capabilities.
Practical Example: Inventory Management Platform
Let’s examine a business inventory management platform built with Java + Spring Boot stack:
- Java – Complex order processing logic and workflows for procurement, logistics
- Spring Boot – APIs for order and inventory management; ecommerce frontends
- Postgres – Relational structure for goods master data, orders, inventory state
- Kafka – Streaming analytics on order trends, product demands
This demonstrates applying the robustness and maturity of Java with the productivity of Spring Boot to deliver reliability at scale – key for business applications.
3. Python + Django/Flask Stack
Key Components: Python, Django/Flask, PostgreSQL/MySQL
The Python + Django/Flask combo has emerged as a very popular back-end stack choice used by many high-traffic sites. It offers:
- Python – Simple, readable general purpose programming language great for web apps
- Django – Full-featured web framework similar to Ruby on Rails
- Flask – Lightweight web framework easy to get started
Some benefits of Python-based web stacks are:
- Quick prototyping and programming due to Python flexibility
- Great libraries and package ecosystem including for ML/AI
- Scalable via WSGI containers, load balancing and asynchronous frameworks
- Cost-efficient by leveraging open source components with no vendor lock-in
The Python stack is great for MVPs and rapid iteration products. In 2024, Python will continue to grow stronger in analytics, AI/ML and cloud-native deployments powering many industry solutions.
Practical Example: Building an AI-powered Knowledge Base
Here’s an example smart knowledge base leveraging the Python stack:
- Python – Scripts for training NLP models to convert user queries into answers
- Flask – Lightweight web tier and REST API layer
- MySQL – Store corpus of documents and intermediate representations
- Elasticsearch – Fast text search and retrieval from documents
- React – Browser-based chat interface powered by Python backend
This showcases Python’s versatility in enabling AI-based products by gluing components for data access, transformation, model training and web services.
Key Components: Go (Golang), Gin, PostgreSQL/MongoDB
The Go + Gin stack is gaining strong momentum driven by trends towards microservices, containers and devops. Key elements include:
- Go – Compiled, statically-typed language great for building high-performance services
- Gin – Web framework similar to Sinatra/Express with good support for REST APIs
- Postgres/MongoDB – Persistence via SQL or NoSQL databases
Benefits of Go-based application development include:
- Speed – Compiled language and efficient concurrency model results in high throughput
- Simplicity – Easy to learn language supporting modern, compact application architecture
- Portability – Single binary deploys making it cloud and container friendly
- Reliability – Statically typed for better robustness with low resource overhead
Go is well suited for engineering scale out services like API gateways, proxies, caches which are crucial for ultra high performance systems. It has great traction in cloud-native development which will further accelerate.
Practical Example: Retail Product API Stack
Here’s an ecommerce product API built with Go + Gin stack:
- Go – Implement cart, checkout and order processing functions; domain entity logic
- Gin – Expose product catalog, inventory and order APIs with middleware
- MongoDB – Persist product details, inventory counts, order documents
- Kafka – Stream order, shipment events to downstream transaction systems
This showcases Golang’s sweet spot in building robust backend APIs and services for distributed systems.
5. Serverless Stack
Key Components: AWS Lambda, DynamoDB, S3, React
The Serverless architecture approach is gaining rapid enterprise adoption, accelerated by cloud vendor offerings. Key enablers are:
- AWS Lambda – Run application logic as functions without managing servers
- DynamoDB – Serverless NoSQL database with auto scaling capacity
- S3 – Scalable object storage integrated with cloud services
- React – Frontend framework for building adaptive user interfaces
Benefits driving serverless adoption are:
- Cost efficiency – Pay per actual consumption reducing resource waste
- Autoscaling – Inbuilt high availability and load balancing
- Acceleration – Rapid experimentation without ops overheads
- Portability – Framework abstractions prevent vendor lock-in
Serverless helps enterprises achieve agility, reduce costs and shifts focus to delivering business value vs. just “keeping the lights on”. It will see increased real world production usage powering a variety of workloads in 2024.
Practical Example: Building a Mobile Voting App
Here’s a mobile voting application built using a serverless stack:
- React Native – Cross platform mobile app with adaptive voting UI screens
- AWS Lambda – Vote processing application logic exposed as API
- DynamoDB – Stores user profiles, votes and poll status
- S3 – Static assets like images hosted efficiently
- API Gateway – Rate limiting, authentication layered on API facade
This showcases the agility and productivity benefits of using managed cloud services to build mobile/web apps fast without provisioning backend servers.
Beyond the top 5, here are some other stacks seeing rising enterprise adoption:
- .NET Core + Azure – Microsoft’s open source web framework and cloud platform
- Vue.js + Hasura – Auto-generating GraphQL APIs accelerating frontend development
- Blockchain Smart Contracts – Programmable trust for fintech/healthcare use cases
Choosing your Tech Stack
When evaluating technology stacks, ensure alignment with both short-term and long-term business objectives. Key considerations include:
- Application needs – Data models, traffic volumes, latency limits, device reach etc.
- Inhouse skills & culture – Engineering talent comfort with technology
- IT strategy – Cloud vs on-prem deployment models, vendor partnerships
- Innovation pipelines – Scope for trying out emerging technologies like blockchain, quantum
Strike the right balance between playing to internal team strengths and accommodating future application modernization initiatives.
While the above stacks provide good starting points, pragmatic adoption driven by clear technical vision and execution roadmaps goes a long way in harnessing stack value especially for larger organizations.
Frequently Asked Questions
Q: Which tech stack is best for machine learning apps?
Python is currently the most popular choice for building and deploying machine learning apps given its extensive data science oriented libraries like NumPy, SciPy and Scikit-Learn.
Q: Are Low-code platforms a viable tech stack option?
Yes, low-code platforms like Appian, Mendix and OutSystems are gaining adoption for rapid enterprise application development and integration projects where coding skill is scarce. They simplify building CRUD apps fast by translating visual models into running code. However, lack of control over architectural choices and risk of vendor lock-in are downsides to factor.
Q: Which databases pair best with serverless architectures?
Purpose built, auto-scaling NoSQL databases like AWS DynamoDB and MongoDB Atlas scale efficiently for serverless applications which have fluctuating traffic patterns. They provide high availability without capacity planning and operational overhead required for running database servers.
Q: Between .NET and Java, which is better suited for legacy modernization?
Both Java and .NET provide good mechanisms for gradual migration of legacy systems like mainframes and vintage ERPs. Java has more experience given its maturity powering legacy modernization over the past decade. .NET Core and Blazor enable lifting legacy UIs into web-based clients efficiently while maintaining backend investments.
Q: Do these stacks lock us into the hyperscaler cloud platforms?
While stacks like serverless and MERN tightly integrate cloud provider services, use of orchestrators like Kubernetes and abstraction layers like Terraform help prevent excessive lock-in. Emerging stacks like Hasura for auto-generating GraphQL also promote cloud neutrality and portability across environments.
Technology transformations can seem intimidating. I hope glimpsing into the stacks driving maximum impact in 2024 provides a compass to help chart application modernization roadmaps aligned with long-term business vision. Let me know if you have any other questions!