Top 10+ Backend Technologies to Use in 2024: Expert Advice

Fernando Doglio · Improve this Guide

Backend technologies are the key to building robust and scalable applications. They power all platforms and products on the web without even being visible to the users.

While backend programming languages form the foundation of backend development, they aren’t enough on their own. Understanding and leveraging the right backend technologies can significantly enhance your development workflow and application performance.

As a backend developer, you’ll be faced with too many options while trying to define your backend technology stack, and that can feel overwhelming.

So, in this article, we’re going to cover the best backend technologies in the following categories:

• Databases
• Version control systems
• Containerization and orchestration
• Cloud platforms
• APIs & Web Services
• Caching systems
• Message brokers
• Authentication and Authorization systems
• CI/CD
• Monitoring & Logging

These should help you stay up-to-date or reach the required level to succeed as a backend developer.

Databases

We can’t have a list of backend technologies to learn without covering databases. After all, databases are a core piece of the best backend technologies in use today and the backbone of any application, providing the necessary storage and retrieval of data. Choosing the right type of database depends on your application’s requirements, such as data consistency, scalability, and complexity.

SQL Databases

SQL databases (or relational databases as they’re also called) bring structure to your data and a standard querying language known as SQL.

PostgreSQL

PostgreSQL is an advanced open-source relational database known for its reliability and extensive feature set. It supports a wide range of data types and complex queries, making it ideal for applications that require ACID compliance and advanced data handling capabilities. PostgreSQL is commonly used in financial systems, data warehousing, and applications needing strong data integrity and complex reporting.

PostgreSQL also offers robust support for JSON and JSONB data types, enabling seamless integration of relational and NoSQL capabilities within a single database system. Its powerful indexing mechanisms ensure efficient query performance even with large datasets.

Additionally, PostgreSQL provides advanced security features like row-level security and multi-factor authentication, making it a secure choice for handling sensitive data.

MySQL

MySQL is a widely used open-source SQL database praised for its speed, reliability, and ease of use. It is particularly popular backend technology for web applications and online transaction processing (OLTP) due to its performance and robust community support. MySQL is often the database of choice for content management systems, e-commerce platforms, and logging applications.

MySQL also supports a variety of storage engines, including InnoDB, which provides ACID compliance, foreign key support, and transaction-safe operations, making it suitable for a wide range of applications.

Its replication capabilities, including master-slave and group replication, ensure high availability and scalability for large-scale deployments. Additionally, MySQL offers advanced security features such as data encryption, user authentication, and role-based access control, enhancing its suitability for handling sensitive data.

Microsoft SQL Server

SQL Server is a relational database management system from Microsoft that offers great performance, scalability, and deep integration with other Microsoft products. It provides comprehensive tools for database management, including advanced analytics and business intelligence features. SQL Server is ideal for enterprise-level applications, data warehousing, and environments where integration with Microsoft services, such as Azure, is beneficial.

MSSQL Server also includes robust security features, such as transparent data encryption, dynamic data masking, and advanced threat protection, making it a trusted choice for handling sensitive data. It supports a wide range of data types, including spatial and XML data, and offers powerful indexing and query optimization techniques to ensure efficient data retrieval and processing.

SQL Server’s integration with Visual Studio and other Microsoft development tools helps to streamline the development process.

SQLite

SQLite is a self-contained, serverless, and zero-configuration database engine known for its simplicity and ease of use. It is lightweight and efficient, making it perfect for small to medium-sized applications, mobile apps, desktop applications, and prototyping. SQLite is embedded within the application, eliminating the need for a separate database server, which simplifies deployment and maintenance. Its single-disk file format makes it highly portable across various operating systems and platforms. SQLite’s efficient memory and disk usage allow it to perform well even on devices with limited resources, such as IoT devices and embedded systems.

This makes SQLite an excellent choice for applications where simplicity, reliability, and low overhead are essential.

NoSQL Databases

On the other hand, NoSQL databases allow for more flexibility by removing the need for a fixed schema and structure to your data. Each solution presented here covers a different type of unstructured database, and it’s up to you to decide if that focus actually makes sense for your business logic or not.

MongoDB

MongoDB is a document-oriented database that offers flexibility and scalability. It handles unstructured data with ease, making it ideal for applications with large-scale data and real-time analytics. MongoDB is commonly used in content management systems, e-commerce platforms, and applications that require a dynamic schema. Its ability to store data in JSON-like documents allows for easy data retrieval and manipulation.

DynamoDB

DynamoDB is a fully managed NoSQL database service provided by AWS. It is designed for high-performance applications requiring seamless scalability and high availability. DynamoDB is best suited for high-traffic web applications, gaming, and IoT applications. Its serverless nature means it can automatically scale up or down based on demand, ensuring consistent performance and cost-efficiency.

Cassandra

Cassandra is an open-source distributed NoSQL database known for its high availability and fault tolerance without compromising performance. It is ideal for large-scale applications and real-time big data analytics. Cassandra’s distributed architecture makes it perfect for environments requiring continuous availability and the ability to handle large amounts of data across multiple nodes. It is commonly used in social media platforms, recommendation engines, and other data-intensive applications.

Version Control Systems

Version control systems are essential for managing changes to source code over time, allowing multiple developers to collaborate effectively and maintain a history of changes.

Git

When it comes to picking the right version control tool, Git is the most widely used one. It provides a powerful, flexible, and distributed model for tracking changes. Git’s architecture supports nonlinear development, allowing multiple branches to be created, merged, and managed independently. This makes Git essential for code collaboration and version tracking, making it a foundational tool for any developer.

Let’s go through some of the key benefits that make Git one of the leading backend technologies in web development.

Distributed Version Control

Unlike centralized version control systems (CVCS) where a single central repository holds the entire project history, Git allows each developer to have a complete copy of the repository, including its history. This decentralized approach enhances collaboration and ensures that work can continue even if the central server is down.

Branching and Merging

Branching: Git’s lightweight branching model allows developers to create, delete, and switch between branches effortlessly. This facilitates isolated development of features, bug fixes, or experiments without impacting the main codebase.

Merging: Git provides powerful merging capabilities to integrate changes from different branches. Tools like merge commits and rebasing help manage and resolve conflicts, ensuring a smooth integration process.

Performance

Git is designed to handle everything from small to very large projects with speed and efficiency. Its performance for both local operations (like committing and branching) and remote operations (like fetching and pushing changes) is optimized, making it suitable for high-performance needs.

Commit History and Tracking

Commit Granularity: Git encourages frequent commits, each with a descriptive message, making it easier to track changes, understand the project history, and identify when and why a change was made.

History Viewing: Commands like git log, git blame, and git bisect allow developers to explore the project’s history, pinpoint the introduction of bugs, and understand the evolution of the codebase.

Collaboration

While strictly not part of Git’s feature set, these functionalities enhance the basic set of features provided by the version control system.

Pull Requests: Platforms like GitHub, GitLab, and Bitbucket build on Git’s capabilities, offering features like pull requests to facilitate code reviews and discussions before integrating changes into the main branch.

Code Reviews: Integrating with continuous integration (CI) systems, Git platforms enable automated testing and code quality checks, ensuring that changes meet project standards before merging.

Staging Area

Git’s staging area (or index) provides an intermediate area where changes can be formatted and reviewed before committing. This allows for more granular control over what changes are included in a commit.

GitHub

GitHub is a web-based platform that leverages Git for version control. It provides an extensive list of collaborative features, including (as already mentioned) pull requests, code reviews, and project management tools.

Key Features and Benefits

Pull Requests and Code Reviews: Facilitate discussions around proposed changes before integrating them into the main codebase. Developers can review code, leave comments, and suggest improvements. Built-in tools for reviewing code changes ensure collaborations are following coding standards and catch potential issues early.

Project Management: GitHub Issues allow tracking of bugs, enhancements, and tasks. Milestones help in organizing issues into targeted releases or sprints. Kanban-style boards provide a visual way to manage tasks, track progress, and organize workflows.

Continuous Integration and Deployment: Automate workflows for CI/CD, testing, deployment, and more. GitHub Actions supports custom scripts and pre-built actions to streamline DevOps processes.

Community and Collaboration: Developers can host static websites directly from a GitHub repository with Github Pages, they’re ideal for project documentation or personal websites. Integrated wikis can be used for detailed project documentation. And through forking, starring, and following repositories the platform encourages collaboration and knowledge sharing.

GitHub’s extensive features and strong community support make it the de facto choice for many companies and developers, both for open-source and private projects.

GitLab

GitLab is a web-based platform for version control using Git, known for its robust CI/CD pipeline integration. It offers a comprehensive set of tools for the entire DevOps lifecycle, making it suitable for continuous integration, deployment, and monitoring.

Key Features and Benefits

Integrated CI/CD: Built-in continuous integration and continuous deployment pipelines allow backend developers to automate building, testing, and deploying code changes. With Gitlabs they can even automatically configure CI/CD pipelines, deploy applications, and monitor performance, all through the same platform.

Security and Compliance: Gitlabs provides key security capabilities for backend development: built-in static and dynamic application security testing (SAST/DAST).

Collaboration and Communication: Instead of Pull Requests like Github, Gitlabs provides the concept of “Merge Requests”: a simplified code review process with inline comments and suggestions.

GitLab’s all-in-one platform makes it an excellent choice for teams looking to streamline their DevOps processes and improve collaboration and productivity.

Bitbucket

Bitbucket is a Git-based source code repository hosting service that provides both commercial plans and free accounts for small teams. It integrates seamlessly with Atlassian products like Jira and Trello, making it a great choice for teams already using these tools.

Repository Hosting: Bitbucket supports both Git and Mercurial version control systems. And it offers unlimited private repositories for teams.

Integration with Atlassian Products: Seamlessly integrates with Jira for issue tracking and project management. It can create branches from Jira issues and view development progress which is a fantastic integration for big teams using both tools. If, on the other hand, you’re using Trello, it can connect to Trello’s boards for visual task management and tracking.

Continuous Integration and Deployment: Integrated CI/CD service for automating builds, tests, and deployments. It can be configured with a YAML file for custom workflows.

Security and Permissions: Control who accesses specific branches to enforce workflows and protect critical branches. You can even enhance security with two-factor authentication.

Bitbucket’s integration with Atlassian’s suite of products, along with its robust CI/CD capabilities, make it an attractive option for teams seeking a tightly integrated development and project management environment.

Containerization and Orchestration

While backend developers aren’t always directly involved in the deployment process, understanding the basics of containerization and orchestration can help them work and interact with the team in charge of devops (who usually set up these CI/CD pipelines).

While this is not an exhaustive list of backend technologies, the two main ones to learn about are:

Docker

Docker is a platform for developing, shipping, and running applications in containers. Containers package software and its dependencies, ensuring it runs consistently across different environments. Docker simplifies application deployment and testing, making it ideal for microservices architectures and continuous integration/continuous deployment (CI/CD) pipelines.

Kubernetes

Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. It orchestrates containers across clusters of machines, providing high availability, scalability, and efficient resource utilization. Kubernetes is perfect for complex, large-scale applications requiring robust infrastructure management and automated scaling.

Cloud Platforms

Cloud platforms provide a range of services and infrastructure that allow developers to deploy, manage, and scale applications without maintaining physical servers. Mind you, the “cloud” is nothing else than someone else’s servers that you don’t have to manage.

These platforms all offer very similar types of managed services (each with its own flavor) that allow you to set up powerful and scalable infrastructures with a few clicks.

Amazon Web Services (AWS)

Amazon Web Services (AWS) is a very complete cloud computing platform offered by Amazon. It provides a broad range of services, including computing power, storage solutions, and databases, catering to various needs and applications.

Key Characteristics of AWS

Scalability: AWS provides scalable solutions that allow businesses to easily adjust resources based on demand. Global Reach: With data centers located worldwide, AWS offers high availability and low latency for global applications.

Diverse Service Offerings: AWS offers a wide range of services, including EC2 for computing, S3 for storage, and RDS for databases.

Security and Compliance: AWS provides robust security features and complies with numerous industry standards and regulations.

Cost Management: Flexible pricing models and cost management tools help businesses optimize their cloud spending.

Google Cloud Platform (GCP)

Google Cloud Platform (GCP) is a suite of cloud computing services provided by Google. Like AWS and Microsoft Azure, GCP offers a variety of services, including computing power, storage, machine learning, and data analytics.

Key Characteristics of GCP

AI and Machine Learning: GCP excels in providing advanced AI and machine learning tools, leveraging Google’s expertise.

Big Data and Analytics: GCP offers powerful analytics tools, including BigQuery, for handling large-scale data processing.

Networking: GCP provides a robust and secure global network infrastructure.

Integration with Google Services: Seamless integration with Google Workspace and other Google services enhances productivity and collaboration.

Open Source Support: GCP supports various open-source technologies, promoting flexibility and innovation.

Microsoft Azure

Microsoft Azure is a cloud computing service created by Microsoft, offering a wide range of cloud services, including those for computing, analytics, storage, and networking.

Key Characteristics of Microsoft Azure

Integration with Microsoft Products: Azure offers seamless integration with popular Microsoft software and services.

Hybrid Cloud Capabilities: Azure supports hybrid cloud environments, enabling smooth integration between on-premises and cloud resources.

Comprehensive Service Range: Azure provides a broad spectrum of services, including Azure Virtual Machines, Azure SQL Database, and Azure DevOps.

Enterprise-Grade Security: Azure emphasizes security with advanced features and compliance with industry standards.

Developer and IT Pro Tools: Azure offers a wide range of tools for developers and IT professionals, including Visual Studio and Azure DevOps.

At a high level, all of these providers are very similar to each other, to the point where backend developers experienced in one of them, can extrapolate their understanding of the environment into others with minimum ramp-up time.

APIs and Web Services

APIs (or Application Programming Interfaces) and web services are another mandatory incorporation to the list of top backend technologies any developer should keep in mind. They enable communication between different software systems.

The three most common types of APIs right now, are REST, GraphQL and gPRC, let’s take a closer look at each one of them.

REST

REST is a standard architecture for web services, known for its simplicity and scalability. It operates on stateless principles and uses standard HTTP methods (GET, POST, PUT, DELETE) to perform CRUD (Create, Read, Update, Delete) operations. RESTful APIs are typically used to access and manipulate web resources using URLs.

REST is ideal for web applications and services due to its ease of implementation and broad compatibility with various web technologies. It is commonly used for developing APIs for web and mobile applications, providing endpoints that clients can interact with to perform various operations. RESTful APIs are also ideal for integrating with third-party services, enabling data exchange and interaction between different systems.

Key Characteristics of REST

Statelessness: Each request from a client contains all the information needed to process the request, without relying on stored context on the server.

Uniform Interface: REST APIs follow standard conventions, making them easy to understand and use. This includes using standard HTTP methods and status codes.

Client-Server Architecture: Separates the client and server concerns, improving scalability and flexibility. Clients handle the user interface and user experience, while servers handle data storage and business logic.

Cacheability: Responses from REST APIs can be cached to improve performance, reducing the need for repeated requests.

Layered System: REST allows for a layered system architecture, enabling intermediaries like load balancers and proxy servers to enhance security, performance, and scalability.

If you’d like to know more about REST, you can read the full definition directly from its source here.

GraphQL

GraphQL is a query language for APIs and a runtime for executing those queries by using a type system you define for your data. Unlike REST, where multiple endpoints return fixed data structures, GraphQL allows clients to request exactly the data they need. This flexibility reduces the amount of data transferred over the network and can significantly improve performance.

GraphQL is ideal for applications with complex and dynamic data requirements.

Key Characteristics of GraphQL

Declarative Data Fetching: Clients specify the structure of the response, ensuring they receive only the data they need.

Strongly Typed Schema: The API schema is strongly typed, providing clear and detailed documentation of available data and operations.

Single Endpoint: Unlike REST, GraphQL uses a single endpoint to serve all requests, simplifying the API architecture.

Real-time Data: Supports real-time updates through subscriptions, enabling clients to receive live data changes.

gRPC

gRPC is a high-performance, open-source RPC (Remote Procedure Call) framework developed by Google. gRPC is designed for low-latency, high-throughput communication, making it suitable for microservices architectures and real-time communication systems.

gRPC is ideal for applications that require efficient, reliable, and bi-directional communication.

Key Characteristics of gRPC

Protocol Buffers: Uses Protocol Buffers for compact, efficient, and platform-neutral serialization of structured data.

HTTP/2: Utilizes HTTP/2 for multiplexing, flow control, header compression, and efficient binary transport.

Bi-directional Streaming: Supports multiple types of streaming, including client-side, server-side, and bi-directional streaming.

Cross-Language Compatibility: Provides support for multiple backend programming languages, enabling interoperability between different systems.

Caching Systems

Caching systems store copies of frequently accessed data to reduce latency and improve application performance. They are essential for speeding up data retrieval and reducing the load on primary data stores.

Implementing a successful caching strategy is not trivial, and one key aspect of it is the backend technology used for the implementation. While there might be multiple options out there, the industry currently recognizes only one de facto choice: Redis.

Redis: a fast in-memory storage solution

Redis is an in-memory data structure store that can function as a database, cache, and message broker. It supports various data structures such as strings, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, and with the right add-ons, even vectors. Redis uses a key-value storage mechanism, which makes it simple yet powerful for a wide range of use cases.

Let’s quickly review some of the characteristics of Redis that make it such a fantastic option.

High Availability and Scalability

• Redis Sentinel: Provides high availability and monitoring, automatically promoting a slave to master in case of failure, ensuring minimal downtime.

• Redis Cluster: Supports automatic sharding, allowing Redis to scale horizontally. It partitions data across multiple nodes, ensuring that the system can handle large datasets and high throughput.

Performance and Use Cases

Redis’s in-memory architecture gives it unmatched I/O speed, making it ideal for real-time applications such as:

• Gaming: Managing leaderboards, player sessions, and real-time statistics.
• Chat Applications: Storing messages, user presence information, and delivering real-time notifications.
• Analytics: Real-time data processing and analytics, where rapid data access and manipulation are crucial.
• Caching: Reducing database load by caching frequently accessed data, improving application response times.

Persistence and Durability

• RDB (Redis Database): Creates snapshots of the dataset at specified intervals, allowing data to be restored from the last snapshot.
• AOF (Append Only File): Logs every write operation received by the server, providing a more durable solution that can replay the log to reconstruct the dataset.
• Hybrid Approach: Combining RDB and AOF to leverage the benefits of both methods, balancing performance and data durability.

Advanced Features

On top of all of that, Redis even provides some very powerful out-of-the-box features:

• Lua Scripting: Supports server-side scripting with Lua, enabling complex operations to be executed atomically.
• Pub/Sub Messaging: Allows for message broadcasting to multiple clients, supporting real-time messaging and notifications. You can create whole event-based architectures around Redis.
• Modules: Extend Redis functionality with custom modules, such as RedisGraph for graph database capabilities and RedisJSON for JSON document storage.

Redis’s robust feature set, combined with its high performance and flexibility, makes it a versatile tool for developers looking to build scalable and responsive applications.

Message Brokers and Streaming Platforms

Message brokers and streaming platforms facilitate communication between different parts of a system, enabling efficient data exchange and processing. They are crucial for building scalable and resilient applications and they are the core of reactive architectures (also known as event-based architectures).

RabbitMQ

RabbitMQ is an open-source message broker that implements the Advanced Message Queuing Protocol (AMQP). It supports multiple messaging protocols and can be deployed in distributed and federated configurations. RabbitMQ is ideal for use cases that require reliable message delivery, complex routing, and interoperability with other messaging systems. It is commonly used in financial systems, order processing, and other applications that need robust messaging capabilities.

Apache Kafka

Apache Kafka is a distributed streaming platform designed for high-throughput, low-latency data processing. It excels at handling real-time data feeds, making it suitable for applications that require continuous data integration and processing. Kafka’s publish-subscribe messaging system is fault-tolerant and scalable, making it ideal for big data applications, real-time analytics, event sourcing, and log aggregation. Its ability to store streams of records in a fault-tolerant manner also makes it useful for building event-driven architectures and microservices.

As backend developers, understanding how to take advantage of these message queues is critical to the development of scalable and resilient platforms. It is definitely a must-have skill and you need to master it.

Authentication and Authorization

Authentication and authorization technologies are essential for securing applications, ensuring that users are who they claim to be and have the appropriate permissions to access resources.

This space is filled with solutions and methodologies, so it’s not easy to pick one option here, however, these two are very common solutions used to implement both, authZ (authorization) and authN (authentication).

OAuth

OAuth is an open standard for access delegation commonly used to grant websites or applications limited access to a user’s information without exposing their passwords. It is widely used in single sign-on (SSO) systems, enabling users to log in to multiple applications with a single set of credentials. OAuth is ideal for third-party applications that need access to user data, such as social media integrations and API access management.

JWT (JSON Web Tokens)

JWT is a compact, URL-safe means of representing claims to be transferred between two parties. The claims in a JWT are encoded as a JSON object, which is used as the payload of a JSON Web Signature (JWS) structure or as the plaintext of a JSON Web Encryption (JWE) structure. JWTs are commonly used for authentication and authorization in web applications, providing a secure way to transmit information between parties. They are particularly useful in stateless authentication systems, where user state is not stored on the server (like when dealing with RESTful APIs).

CI/CD Pipelines

CI/CD (Continuous Integration/Continuous Deployment) pipelines automate the process of code integration, testing, and deployment, enabling faster and more reliable software delivery. This is one of the key areas backend developers need to understand to avoid creating code that simply gets in the way of the deployment process.

GitHub Actions

GitHub Actions is an integrated CI/CD service within GitHub repositories, allowing developers to automate build, test, and deployment workflows. It supports a wide range of actions and integrations, making it highly customizable and versatile for various development workflows.

CircleCI

CircleCI is a continuous integration and delivery platform that automates the building, testing, and deployment of applications. It supports multiple backend languages and integrates with various version control systems, making it a popular choice for diverse development environments. CircleCI is known for its speed and ease of setup, providing robust tools for optimizing and monitoring CI/CD pipelines.

GitLab CI/CD

GitLab CI/CD is an integrated part of the GitLab platform (similar to how GitHub actions are a part of GitHub), offering continuous integration, delivery, and deployment features within the GitLab ecosystem. It allows developers to manage their entire DevOps lifecycle in a single application, from planning and coding to monitoring and security. GitLab CI/CD is particularly useful for teams seeking a seamless and comprehensive CI/CD solution.

Jenkins

If instead of a SaaS, you’re looking for a solution that you can potentially self-host, then you might want to look into Jenkins. Jenkins is an open-source automation server that provides hundreds of plugins to support building, deploying, and automating your software development process. It is highly extensible and can be integrated with a wide array of tools and technologies. Jenkins is ideal for complex, large-scale projects requiring a customizable and powerful CI/CD environment.

Monitoring and Logging

Understanding how the systems that you develop behave and perform on a daily basis is crucial to launching a successful product. Here’s where monitoring and logging come into play. Monitoring and logging are crucial pieces of backend technology used for maintaining the health, performance, and security of applications. These tools help detect issues, analyze performance, and ensure system reliability.

ELK Stack (Elasticsearch, Logstash, Kibana)

The ELK Stack is a set of tools for searching, analyzing, and visualizing log data in real time. Elasticsearch is a search and analytics engine, Logstash is a server-side data processing pipeline, and Kibana is a visualization tool. Together, they provide a powerful platform for centralized logging and monitoring, making them ideal for applications requiring detailed log analysis and real-time insights.

Grafana

Grafana is an open-source platform for monitoring and observability that integrates with various data sources. It provides powerful visualizations, dashboards, and alerting capabilities, making it a popular choice for monitoring infrastructure and application performance. Grafana is particularly useful for teams needing a flexible and customizable monitoring solution.

Loki

Loki is a log aggregation system designed to work with Grafana. It is optimized for cost-effective and scalable logging, making it suitable for applications with high log volumes. Loki simplifies log management by allowing developers to query logs using the same language as Grafana, providing seamless integration for comprehensive observability.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. It collects and stores metrics as time series data, providing powerful querying language and alerting capabilities. Prometheus is ideal for monitoring applications and infrastructure, particularly in cloud-native and microservices environments, where dynamic and ephemeral resources are common.

In the end, you might want to go with one or several of these options, the point is that you, as a developer, should be aware of them and what type of value they add to the project.

Conclusion

As backend developers, focusing on a backend programming language and a backend framework is not going to be enough. The backend ecosystem is very rich, and there are many areas that are either directly or indirectly related to the daily tasks that a backend dev needs to work on.

This is why you need to stay up-to-date and look at the trends that develop within each area to make sure you’re still working with and focusing on the right solutions.

If you’d like more details on the type of backend development technologies you should be focusing on to excel at your role as a backend developer, check out our Backend Developer roadmap.