Crypto Basics

Cardano (ADA) Crypto – What It Is and How It Works?

Learn everything about Cardano (ADA) crypto and how it works in this descriptive guide.
Token Metrics Team
8 minutes
MIN

Cardano (ADA) can be described as a blockchain platform that’s designed to enable the development of decentralized applications and smart contracts. It is the first blockchain platform to be built on a scientific philosophy and to be developed through peer-reviewed research and scientific rigor. Developed by a global team of leading researchers and engineers, Cardano is set to revolutionize the way we use and interact with blockchain technology. 

This beginner's guide to Cardano will provide you with all the information you need to understand the platform, its features, and how to use it. From its unique consensus algorithm to its native token ADA, this guide will provide you with a comprehensive overview of Cardano. Whether you're a beginner interested in learning more about Cardano or a blockchain expert looking for the latest information, this guide has you covered from end-to-end. 

History of Cardano

Cardano was founded by Charles Hoskinson, who also co-founded Ethereum. However, Cardano is a very different platform from Ethereum regarding its design and goals. Whereas Ethereum is a decentralized application ("dapp") platform designed to power all sorts of different decentralized applications, Cardano is designed to be a "first generation" blockchain platform that can be used to build decentralized applications, as well as other things.

The Cardano Foundation, IOHK, and Emurgo are developing the Cardano platform. The three groups are working together to build the Cardano platform and will hold a stake in the Cardano ecosystem. 

The first phase of Cardano's development began in 2015. At the time, a company called Input-Output (IOHK) was contracted to build the platform. In 2017, IOHK decided to hand over control of the project to the Cardano Foundation and Emurgo. The three partners are now working together to bring Cardano to market. The next development phase has been completed sometime between 2020 and 2021. After that, Cardano emerged as a fully decentralized blockchain.

How Does Cardano Work?

The Cardano platform uses a proof of stake (PoS) consensus algorithm to manage its decentralized network. Proof of stake is a consensus algorithm where the right to add new blocks to the blockchain is determined not by computing power but by coin ownership. In PoS-based blockchains, users must "stake" or "deposit" their coins to add new blocks to the blockchain for a certain amount of time. The more coins a user stakes, the greater the chance that the user will be selected to add a new block. Cardano uses the Ouroboros proof of stake algorithm. 

Ouroboros is the first proof of stake algorithm to be proven secure in a peer-reviewed paper. This unique algorithm uses a "random selection of a catch-up fellow" to create a network with no central authority. In other words, no single person or group can control the network. The algorithm works by randomly selecting a "follower" who can "catch up" with the "leader."

The leader is the person responsible for adding new blocks to the blockchain. The follower has one job: to predict what the leader will do. If the follower is correct, they are promoted to the leader and given a chance to add a new block. If the follower is incorrect, they remain a follower, and another random person is selected to catch up. The Ouroboros algorithm was expected to be completed by June 2020. But, according to recent reports, Charles Hoskinson said that the Ouroboros Genesis implementation will be in 2023.

Cardano's Development and Governance

The development and governance of Cardano are handled by three large organizations:

The Cardano Foundation: The Cardano Foundation maintains Cardano's core. This group promotes the platform, manages its marketing and communications, and defends the brand.

IOHK: IOHK leads the team behind Cardano's core. This group is responsible for developing and maintaining the platform's core software and bringing new features to the market.

Emurgo: The third group, Emurgo, brings businesses and investments to the Cardano ecosystem. Emurgo helps businesses integrate with the Cardano network and encourages others to build projects on the Cardano platform.

The functioning of Cardano stands tall because of the highly secured and powerful ecosystem as mentioned above. Now, what is Cardano’s native token ADA?

Cardano's Native Token - ADA

Cardano's native token, ADA, sends money on the Cardano blockchain. It also rewards people who help maintain and build the network. The team behind Cardano has stated that ADA is more than just a token: it also serves as "the fuel that drives the Cardano ecosystem." Cardano’s development team has stated that the platform will be fully decentralized once the network has been around for a few years. Until then, the platform will be maintained by a group of stakeholders who have a vested interest in the platform's success. These stakeholders have a stake in the system and are rewarded with ADA for helping maintain the platform. 

There are 3-easy ways to earn ADA

  • Hosting a node, 
  • Providing software assurance, or 
  • Contributing to the development of Cardano's software or research.

Apart from these, Cardano’s powerful 3-layered ecosystem makes it reliable and trustworthy. 

The 3-Layered Cardano's Ecosystem

Here are the three secured-layers that constitute Cardano (ADA): 

The Cardano Network: The Cardano network is the blockchain that runs the ADA token and smart contracts. It is maintained by the stakeholders, who receive ADA for their work.

Cardano's core technology: The Cardano core represents the core software that powers the Cardano network. This includes the programming languages used to build decentralized applications and the virtual machine that runs those apps.

All the projects built on top of the Cardano platform: The Cardano projects layer lists all the decentralized applications built on top of the Cardano network.
To top it all, you can also enjoy the benefit of smart contracts on Cardano. 

Smart Contracts On Cardano

Although Cardano is designed to be a dapp platform, it can also be used to build smart contracts. The programming language used to build smart contracts on Cardano is called Haskell and Cardano's virtual machine, called the "Computing Resources And Dispatcher" (CRDD), can execute many programming languages.

Any decentralized application built in any programming language can be hosted on the Cardano network. Cardano's smart contracts are unique because they are the first to be verified by a formal verification tool called the "Industrial Strength Verification" (ISV). This tool will help you confirm whether or not a smart contract is safe to use.

Cardano's Use Cases

Use Case #1: The first use case for Cardano is a decentralized application platform. This means that developers can build apps on top of the Cardano blockchain. These dapps will be able to send and receive ADA and use other features like the ability to create a wallet or sign a transaction. 

Use Case #2: The second use case for Cardano is as a financial asset. Investors can buy and sell ADA on cryptocurrency exchanges, and the token could also represent ownership in a company.

Now, let’s see the security measures that Cardano aims to offer.

Security on Cardano

One of the most common questions about Cardano is how secure it is compared to other blockchains. Cardano does not claim to be more secure than other blockchains but seeks to be as secure as possible. The team behind Cardano has said that one of their goals is to be the "safest and most reliable blockchain." 

One way Cardano strives to be more secure is through its unique design. While other blockchains are designed to do one thing well, Cardano is designed to do many different things less well. Cardano's design means no single platform part is crucial to its operation. If one part of the platform fails, many other parts can take its place. This indicates safety at its best.

Is Cardano a Worthy Investment?

There we are swinging again to whether or not Cardano is a good investment. Let’s check out the latest updates before we decide, shall we?

According to the Cryptoglobe’s Report, ADA’s price might soar up to 100% by 31st January, 2023. Major upgrades are being anticipated by investors to improve DeFi’s significance through its oracles.

So, Cardano is something to look forward to owing to its upcoming features. 

Future of Cardano

Let’s dive a bit further into the future. Cryptopolitan thinks the price of ADA will soar up to $21.35 on an average, with a minimum price of $20.55. Changelly also believes that ADA price will rise, but the website thinks the coin price will only peak at $15.69, with an average of $13.92, similar to the data from Price Prediction. The website’s analysts predict that the coin’s maximum price will be $15.69 with a minimum of $13.55.

Most experts predict that Cardano might see a bright future in 2023. With persistent developments Cardano’s ecosystem has been witnessing, and in the crypto asset market as a whole, Cardano can potentially reach a new high.

The Bottom Line

Cardano aims to be a "first generation" blockchain technology. The platform is being built by a group of organizations, each with a specific role in the project.

The team hopes this design will help Cardano achieve its goal of being the most secure blockchain. The platform uses a unique consensus algorithm, and its native token is storable in various wallets. The token can be used to represent ownership in a company. 

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APIs Explained: How Application Programming Interfaces Work

Token Metrics Team
5
MIN

APIs are the invisible glue that connects modern software: they let apps talk to services, fetch data, and automate workflows. Understanding what an API is and how it operates helps developers, analysts, and product teams design integrations that are robust, secure, and scalable.

What is an API? Definition, scope, and common types

An API, or application programming interface, is a defined set of rules and contracts that allow one software component to interact with another. At a basic level an API specifies the inputs (requests), outputs (responses), and the behavior expected when an operation is invoked. APIs can be exposed within a single application, between services inside a private network, or publicly for third-party developers.

Common API types include:

  • Web APIs (HTTP/HTTPS based, using REST or GraphQL) for browser, server, and mobile communication.
  • RPC and gRPC for high-performance binary communication between microservices.
  • Library or SDK APIs that surface methods within a language runtime.
  • Hardware APIs that expose device functionalities (e.g., sensors, GPU).
  • On-chain and crypto APIs that provide blockchain data, transaction broadcasting, and wallet interactions.

How APIs work: requests, endpoints, and protocols

APIs typically operate over a transport protocol with defined endpoints and methods. In HTTP-based APIs a client sends a request to an endpoint (URL) using methods like GET, POST, PUT, DELETE. The server processes that request and returns a response, often encoded as JSON or XML.

Key components to understand:

  • Endpoint: A specific URL or route that exposes a resource or operation.
  • Method: The action type (read, create, update, delete).
  • Schema / Contract: The shape of request and response payloads, headers, and status codes.
  • Authentication: How the API verifies the caller (API keys, OAuth tokens, signed requests).
  • Rate limits: Rules that prevent abuse by limiting request volume.

Protocols and styles (REST, GraphQL, gRPC) trade off simplicity, flexibility, and performance. REST emphasizes resource-based URLs and uniform verbs. GraphQL offers flexible queries from a single endpoint. gRPC uses binary protocols for lower latency and stronger typing.

Use cases and real-world examples (web, mobile, crypto, AI)

APIs appear in nearly every digital product. Typical use cases include:

  • Web & Mobile Apps: Fetching user profiles, submitting forms, or streaming media from cloud services.
  • Third-party Integrations: Payment providers, identity, and analytics platforms expose APIs to connect services.
  • Crypto & Blockchain: Nodes, indexers, and market data providers expose APIs to read chain state, broadcast transactions, or retrieve price feeds.
  • AI & Data Pipelines: Models and data services expose inference endpoints and training data APIs to enable programmatic access.

For analysts and product teams, APIs make it possible to automate data collection and combine signals from multiple services. AI-driven research tools such as Token Metrics rely on API feeds to aggregate prices, on-chain metrics, and model outputs so users can build informed analytics workflows.

Design, security, and operational best practices

Well-designed APIs are predictable, versioned, and documented. Consider these practical guidelines:

  1. Design for clarity: Use consistent naming, predictable status codes, and clear error messages.
  2. Versioning: Provide v1/v2 in paths or headers so breaking changes don’t disrupt clients.
  3. Rate limiting and quotas: Protect backend resources and provide transparent limits.
  4. Authentication & Authorization: Use proven schemes (OAuth2, signed tokens) and enforce least privilege.
  5. Input validation and sanitization: Defend against injection and malformed payloads.
  6. Observability: Implement logging, metrics, and distributed tracing to monitor performance and troubleshoot failures.
  7. Documentation and SDKs: Publish clear docs, example requests, and client libraries to reduce integration friction.

Security in particular requires ongoing attention: rotate credentials, monitor for anomalous traffic, and apply patching for underlying platforms. For teams building systems that depend on multiple external APIs, plan for retries, exponential backoff, and graceful degradation when a provider is slow or unavailable.

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FAQ: What is an API?

Q1: What is the difference between an API and an SDK?

An API is a contract that defines how to interact with a service. An SDK is a packaged set of tools, libraries, and helpers that implement or wrap that API for a specific language or platform.

How do REST and GraphQL differ?

REST uses multiple endpoints and standard HTTP verbs to model resources; GraphQL exposes a single endpoint where clients request exactly the fields they need. REST is simpler; GraphQL can reduce over-fetching but adds query complexity.

Can APIs return real-time data?

Yes. Real-time patterns include WebSockets, server-sent events, or streaming gRPC. Polling a REST endpoint is simpler but less efficient for high-frequency updates.

What are common API security measures?

Common measures include strong authentication (OAuth2, API keys), TLS encryption, rate limiting, input validation, signed requests, and robust monitoring for abuse or anomalies.

How should teams evaluate third-party APIs?

Assess uptime history, SLAs, documentation quality, rate limits, pricing model, security posture, and whether the API provides the required schemas and latency characteristics for your use case.

Can APIs be used with AI applications?

Yes. AI models often expose inference APIs for serving predictions, and research tools consume multiple APIs to aggregate training data, features, or market signals. Designing for reproducibility and input validation is important when feeding models with API-derived data.

Disclaimer

This article is educational and informational in nature. It does not provide investment, legal, or professional advice. Implementations and integrations described here are technical examples and should be validated in your environment before deployment.

Research

Understanding APIs: A Practical Guide

Token Metrics Team
6
MIN

APIs power modern software by letting systems communicate without sharing internal code. Whether you use a weather app, social login, or an AI assistant, APIs are the invisible glue connecting services. This guide explains what an API is, how APIs work, practical use cases (including crypto and AI), and criteria to evaluate an API for research or product use.

What is an API? A clear definition

API stands for Application Programming Interface. At its simplest, an API is a set of rules and protocols that lets one program request services or data from another. Think of an API as a restaurant menu: the menu lists dishes (endpoints) you can order (requests), the kitchen prepares the dish (service), and the waiter delivers it to your table (response). The consumer of the API doesn’t see how the kitchen is organized; it only needs to know how to order.

APIs abstract complexity, standardize interactions, and enable modular design. They exist at many layers — from operating systems and libraries to web services that return JSON or XML. For developers and researchers, APIs are indispensable for integrating external data, automating workflows, and composing distributed systems.

How APIs work: architecture, formats, and types

Most modern web APIs follow request/response patterns over HTTP. Key concepts include:

  • Endpoints: URL paths that expose specific resources or actions, e.g., /prices or /users.
  • Methods: HTTP verbs like GET (retrieve), POST (create), PUT/PATCH (update), DELETE (remove).
  • Payloads: Data sent or received, often formatted as JSON for web APIs.
  • Authentication: API keys, OAuth tokens, or signed requests to control access.

Architectural styles and protocols include REST (resource-oriented, stateless), GraphQL (client-specified queries), gRPC (binary, streaming), and WebSockets (persistent full-duplex connections). Each has trade-offs: REST is simple and cache-friendly; GraphQL reduces over-fetching but can complicate caching; gRPC excels in performance for internal microservices.

APIs in crypto and AI: data, execution, and agents

In crypto and AI ecosystems, APIs serve several roles:

  • Market data APIs: Provide price feeds, order book snapshots, historical candles, and index data used for analysis and visualization.
  • Blockchain & on-chain APIs: Expose transaction data, smart contract interactions, wallet balances, and event logs for on-chain analysis.
  • Execution/trading APIs: Let platforms submit orders, query trade status, and manage accounts. These require strict auth and latency considerations.
  • AI & model APIs: Offer inference services, embeddings, or model orchestration endpoints for tasks like NLP, classification, or agent behavior.

Combining these APIs enables product capabilities such as automated research pipelines, AI agents that react to market signals, and dashboards that mix on-chain metrics with model-driven insights. Many teams use dedicated crypto APIs to aggregate exchange and chain data, and AI-driven tools to surface patterns without exposing trading recommendations.

For example, researchers might ingest price and on-chain feeds through a market API, compute custom signals with an AI model, and expose those signals via an internal API for front-end consumption. When evaluating providers, consider freshness of data, coverage across assets/chains, and documented latency characteristics.

How to evaluate, integrate, and maintain APIs

Choosing and integrating an API is not just about endpoints. Use a checklist that covers technical, operational, and governance concerns:

  1. Documentation quality: Look for clear examples, error codes, and sandbox endpoints for testing.
  2. Authentication and security: Prefer APIs that support scoped keys, granular permissions, and strong transport security (TLS).
  3. Rate limits & pricing: Understand request quotas, burst limits, and throttling behavior to design backoff strategies.
  4. Data guarantees: Check latency, update frequency, historical depth, and whether data is normalized across sources.
  5. SLA and reliability: Uptime history, status pages, and support SLAs matter for production use.
  6. Monitoring & observability: Log requests, track error rates, and monitor latency to detect regressions or abuse.

Integration tips: start with a sandbox key, write thin adapters to isolate provider-specific formats, and implement exponential backoff with jitter for retries. For analytics workflows, cache immutable historical responses and only refresh dynamic endpoints when necessary.

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FAQ: common questions about APIs

What is the difference between REST and GraphQL?

REST exposes resources through fixed endpoints and relies on HTTP methods. GraphQL lets clients specify exactly what fields they need in a single query. REST is simpler and benefits from existing HTTP caching; GraphQL reduces over-fetching but can require more complex server-side tooling.

How do API keys and OAuth differ?

API keys are simple tokens issued to clients, often for server-to-server access or basic identification. OAuth is an authorization framework that issues scoped access tokens on behalf of users, enabling delegated permissions and better control over access lifecycle.

What are common API failure modes to plan for?

Rate limiting, transient network errors, schema changes, and authentication failures are typical. Design clients to retry with exponential backoff, validate responses, and fail gracefully when dependencies are degraded.

How can I secure sensitive data when using third-party APIs?

Use encrypted transport (TLS), rotate credentials regularly, scope keys to minimum permissions, and avoid embedding secrets in client-side code. For sensitive workflows, consider a server-side proxy that enforces access policies and masking.

Can AI models be accessed via APIs and how does that affect workflows?

Yes. Many AI models expose inference and embedding endpoints. Using model APIs decouples compute from your product stack, simplifies scaling, and enables A/B testing of models. Evaluate latency, cost per request, and data retention policies when choosing a provider.

How do I test and validate an API integration?

Start in a sandbox environment, create automated integration tests covering success and failure cases, mock third-party responses for unit tests, and run load tests against rate limits. Monitor post-deployment with health checks and alerts.

What are rate limits and how should clients handle them?

Rate limits cap how many requests a client can make in a time window. Clients should respect headers that indicate remaining quota, implement exponential backoff with jitter on 429 responses, and batch requests or cache results when possible.

When should I build my own API versus using a third-party API?

Use a third-party API for non-core data or services where speed-to-market and maintenance offload matter. Build an internal API when the capability is strategic, requires proprietary processing, or when you need tight control over latency, privacy, and SLAs.

How can tools like Token Metrics help with API-driven research?

Data and model platforms can centralize feeds, normalize formats, and provide analytical signals that reduce the engineering overhead of assembling multiple APIs. Token Metrics is an example of a platform that merges model-driven insights with market and on-chain data for research workflows.

Disclaimer

This content is for educational and informational purposes only. It does not constitute financial, legal, or investment advice. Evaluate APIs and services independently and consult appropriate professionals for decisions that involve risk.

Research

APIs Explained: How They Power Apps and AI

Token Metrics Team
6
MIN

APIs are the invisible connectors that let software talk to software. Whether you book a flight, check a crypto price, or ask an AI agent to summarize a document, APIs are likely working behind the scenes. This guide breaks down what an API is, how it works, common types and use cases, and practical steps for research and integration.

What is an API?

An API, or application programming interface, is a defined set of rules and data structures that lets one software component request services or data from another. Think of an API as a contract: the provider exposes endpoints and data formats, and the consumer uses those endpoints to perform actions or retrieve information. This abstraction hides implementation details, enabling interoperability and composability across systems.

At its core, an API specifies:

  • Available operations (endpoints) and accepted parameters
  • Request and response formats (JSON, XML, etc.)
  • Authentication and rate limits
  • Error handling and status codes

APIs accelerate development by allowing teams to reuse services instead of rebuilding functionality. They also enable ecosystems: marketplaces, integrations, and data sharing across organizations.

How APIs Work: Components & Protocols

APIs are implemented over protocols and architectural styles. The most common is REST (Representational State Transfer), which uses HTTP verbs (GET, POST, PUT, DELETE) and URIs to model resources. Alternatives like GraphQL let clients request specific data shapes, which can reduce over- and under-fetching in complex applications.

Key components to understand:

  • Endpoint: A URL representing a resource or action (e.g., /api/v1/prices).
  • Method: The HTTP action to perform (GET to read, POST to create).
  • Payload: The body of a request for create/update operations, usually JSON.
  • Authentication: API keys, OAuth tokens, or other schemes control access.
  • Rate limits: Providers throttle requests to protect services.

Beyond REST and GraphQL, there are webhooks (server-to-server push notifications), gRPC for high-performance RPC-style communication, and socket-based APIs for real-time streams. The choice of protocol affects latency, throughput, and developer ergonomics.

Types of APIs and Real-World Use Cases

APIs come in several flavors depending on visibility and purpose:

  • Public APIs: Exposed to external developers for integrations and apps.
  • Private APIs: Internal to an organization, used to modularize services.
  • Partner APIs: Shared with selected partners under specific agreements.

Common use cases illustrate how APIs deliver value:

  • Payment processing APIs enable e-commerce sites to accept credit cards without storing sensitive data.
  • Mapping and location APIs power ride-hailing, logistics, and geofencing features.
  • Data APIs supply market prices, on-chain metrics, or social feeds for dashboards and trading bots.
  • AI and ML model APIs let applications delegate tasks like transcription, summarization, or image analysis to cloud services.

For example, crypto applications rely heavily on exchange and on-chain data APIs to aggregate prices, monitor wallets, and execute analytics at scale. Evaluating latency, historical coverage, and data quality is critical when selecting a provider for time-series or transactional data.

How Developers and AI Use APIs

Developers use APIs to compose microservices, integrate third-party functionality, and automate workflows. For AI systems, APIs are essential both to access model inference and to fetch context data that models use as inputs.

Practical patterns include:

  1. Chaining: Calling multiple APIs in sequence to enrich a response (e.g., fetch user profile, then fetch personalized recommendations).
  2. Caching: Store frequent responses to reduce latency and cost.
  3. Bulk vs. Stream: Use batch endpoints for historical backfills and streaming/webhooks for real-time events.

When integrating APIs for analytics or AI, consider data consistency, schema evolution, and error semantics. Tools and platforms can monitor usage, surface anomalies, and provide fallbacks for degraded endpoints.

For researchers and teams assessing providers, structured evaluations help: compare SLA terms, data freshness, query flexibility, cost per request, and developer experience. Platforms that combine market data with AI-driven signals can accelerate exploratory analysis; for example, Token Metrics provides AI-backed research and ratings that teams often use to prioritize datasets and hypothesis testing.

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FAQ — What is an API?

Q1: What is the difference between an API and a library?

An API defines a set of rules and endpoints for interaction between systems, often over a network. A library is a local collection of functions and classes that an application links to at runtime. Libraries run in-process; APIs often run across processes or machines.

FAQ — How secure are APIs?

Q2: How should APIs be secured?

Common security measures include authentication (API keys, OAuth), encryption (TLS), input validation, rate limiting, and monitoring for anomalous patterns. Security practices should match the sensitivity of data and regulatory requirements.

FAQ — REST vs. GraphQL

Q3: When to choose REST over GraphQL?

REST is simple and well-suited to resource-based designs and caching. GraphQL is useful when clients need precise control over returned fields and want to minimize round trips. The right choice depends on client needs, caching strategy, and team expertise.

FAQ — What drives API costs?

Q4: What factors affect API pricing?

Pricing typically depends on request volume, data granularity, retention of historical data, and premium features such as websockets, SLAs, or enriched analytics. Evaluate costs under realistic usage patterns and spikes.

FAQ — How to get started with an API?

Q5: How do I evaluate and integrate a new API?

Start by reading docs, testing sandbox endpoints, and estimating request volumes. Validate data formats, authentication flows, and edge cases (rate limits, errors). Prototype with small workloads before committing to production usage.

FAQ — Are APIs regulated?

Q6: Do APIs involve legal or compliance considerations?

APIs that handle personal data, financial transactions, or regulated assets may be subject to privacy laws, financial regulations, or contractual obligations. Assess compliance requirements, data residency, and logging needs early in the design process.

Disclaimer

This article is for educational purposes only and does not constitute investment, legal, or professional advice. Information contained here is neutral and analytical; always perform independent research and consult qualified professionals for decisions involving legal or financial risk.

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