Crypto Basics

Types of Stablecoins: A Complete Guide for 2025

Discover the types of stablecoins—fiat-backed, crypto-backed, algorithmic, and commodity-based. Learn how they work, their pros and cons, and which is best for your crypto strategy in 2025.
Token Metrics Team
8 min
MIN

The cryptocurrency market is famous for volatility—Bitcoin can swing by thousands of dollars in a day, and altcoins can rise or crash in hours. But what if you need price stability? That’s where stablecoins come in.

Stablecoins are digital currencies pegged to stable assets like the US dollar, gold, or even algorithmically maintained price levels. They bridge the gap between the speed and efficiency of blockchain technology and the reliability of traditional money.

As of 2025, stablecoins account for over $140 billion in circulating supply, making them essential for traders, investors, and decentralized finance (DeFi) users. But not all stablecoins are the same—different types use different mechanisms to maintain their stability, each with unique pros and cons.

In this guide, we’ll break down the types of stablecoins, how they work, their risks, and which might be best for your needs.

What Are Stablecoins?

A stablecoin is a cryptocurrency designed to maintain a stable value by pegging its price to a reference asset. Most stablecoins are pegged to fiat currencies like the U.S. dollar (e.g., 1 USDT ≈ $1), but some track commodities (like gold) or are algorithmically balanced to hold value.

They are widely used for:

  • Trading: Moving quickly in and out of volatile assets.
  • DeFi: Providing liquidity, borrowing, and earning yields.
  • Remittances: Sending low-cost, fast cross-border payments.
  • Hedging: Protecting against crypto market volatility.

Types of Stablecoins

There are four main types of stablecoins:

  1. Fiat‑Collateralized Stablecoins
  2. Crypto‑Collateralized Stablecoins
  3. Algorithmic (Non‑Collateralized) Stablecoins
  4. Commodity‑Backed Stablecoins

Each has a different method of maintaining its peg. Let’s break them down.

1. Fiat‑Collateralized Stablecoins

Definition:
These are backed 1:1 by traditional currencies like the U.S. dollar, euro, or yen. For every stablecoin issued, an equivalent amount of fiat is held in reserve by a trusted custodian.

How They Work:
If you buy 1 USDC, Circle (its issuer) holds $1 in a regulated bank account or short-term U.S. Treasury securities. When you redeem that stablecoin, the issuer sends you the equivalent amount in fiat and burns the coin.

Examples:

  • Tether (USDT) – Largest stablecoin by market cap; widely used on exchanges.
  • USD Coin (USDC) – Issued by Circle, fully regulated and audited.
  • TrueUSD (TUSD) – Offers real-time attestation of reserves.
  • PayPal USD (PYUSD) – Launched by PayPal for payments and DeFi.

Pros:

  • High stability – Pegged directly to fiat.
  • Transparent – Many provide audits and attestations.
  • Easy adoption – Ideal for traders, merchants, and payment platforms.

Cons:

  • Centralization – Custodians control reserves and can freeze accounts.
  • Regulatory risks – Subject to government oversight.
  • Less transparency for some issuers – (e.g., Tether faced scrutiny over its reserves).

2. Crypto‑Collateralized Stablecoins

Definition:
These are backed by cryptocurrencies like Ethereum or Bitcoin instead of fiat. Because crypto is volatile, these stablecoins are overcollateralized (e.g., $150 in ETH backs $100 in stablecoins).

How They Work:
When you mint a crypto-backed stablecoin like DAI, you deposit collateral (e.g., ETH) into a smart contract. If the collateral value drops too much, the contract automatically liquidates some assets to maintain the peg.

Examples:

  • DAI – Issued by MakerDAO, backed by ETH, USDC, and other assets.


  • sUSD – A synthetic USD issued by Synthetix.
  • MIM (Magic Internet Money) – Collateralized by multiple crypto assets.

Pros:

  • Decentralized – No single company controls reserves.
  • Transparent – All collateral balances are viewable on-chain.
  • Resistant to censorship – Issuers can’t freeze accounts.

Cons:

  • Volatility risk – Collateral can lose value quickly, requiring liquidations.
  • Overcollateralization – Ties up more capital than fiat-backed options.
  • Complexity – Requires understanding of DeFi mechanics.

3. Algorithmic (Non‑Collateralized) Stablecoins

Definition:
These don’t use physical reserves. Instead, they maintain their peg via algorithmic supply adjustments—minting or burning tokens to balance price around $1.

How They Work:
If demand increases and the price rises above $1, the protocol mints more coins. If it falls below $1, the protocol burns coins or incentivizes users to buy them back.

Examples:

  • Ampleforth (AMPL) – Elastic supply adjusts daily.
  • UST (TerraUSD) – Infamously collapsed in 2022 after its peg broke.
  • Frax (FRAX) – Uses a hybrid model: partly collateralized, partly algorithmic.

Pros:

  • Highly capital-efficient – Doesn’t require large reserves.
  • Decentralized – Often governed by smart contracts and DAOs.

Cons:

  • Peg instability – Prone to “death spirals” when market confidence drops.
  • Complex mechanisms – Harder for average users to understand.
  • History of failures – UST/LUNA crash eroded trust in algorithmic coins.

4. Commodity‑Backed Stablecoins

Definition:
These stablecoins are pegged to commodities like gold, silver, or oil, giving them intrinsic value beyond fiat.

How They Work:
For every coin issued, an equivalent amount of the commodity is held in a secure vault. For example, owning 1 PAX Gold (PAXG) means you own 1 troy ounce of physical gold stored by the issuer.

Examples:

  • PAX Gold (PAXG) – Backed by physical gold.


  • Tether Gold (XAUT) – Gold-backed token from Tether.
  • Digix Gold (DGX) – Pegged to gold bars in Singapore vaults.

Pros:

  • Hedge against inflation – Commodities like gold retain value during economic uncertainty.
  • Diversification – Offers exposure to both crypto and commodities.

Cons:

  • Low liquidity – Less widely used than fiat-backed stablecoins.
  • Storage & audit challenges – Requires trust in the issuer to maintain reserves.

Why Do Stablecoins Matter?

Stablecoins are the backbone of DeFi and crypto trading.

  • Trading & arbitrage: They provide a quick way to exit volatile positions without converting back to fiat.
  • Cross-border payments: Cheaper and faster than SWIFT or remittance services.
  • DeFi participation: Essential for lending, borrowing, yield farming, and liquidity pools.
  • On-ramp/off-ramp: They simplify converting between traditional finance and blockchain.

Which Type of Stablecoin Should You Use?

If you want simplicity & security: Go with fiat-backed coins like USDC or PYUSD.

If you value decentralization: Choose crypto-collateralized options like DAI.

If you’re comfortable with high risk: Explore algorithmic models like FRAX (but beware of peg risks).

If you want inflation protection: Consider commodity-backed coins like PAXG.

Key Risks of Stablecoins

  • Regulation: Governments are increasing oversight of fiat-backed coins.
  • Centralization: Some issuers can freeze funds or blacklist wallets.
  • Smart contract risks: DeFi-based stablecoins can suffer from bugs or exploits.
  • Peg breaks: Algorithmic models are especially vulnerable to confidence loss.

The Future of Stablecoins

In 2025, stablecoins are evolving to meet regulatory and market demands:

  • Central Bank Digital Currencies (CBDCs): Governments are issuing digital dollars and euros, potentially competing with stablecoins.
  • Regulated issuers: Projects like USDC are working closely with regulators to ensure compliance.
  • Hybrid models: Combining fiat and algorithmic elements (e.g., Frax) to enhance stability.

As DeFi expands and global adoption grows, stablecoins will remain at the heart of crypto finance.

Final Thoughts

Stablecoins are more than just “digital dollars.” They’re a critical bridge between traditional finance and blockchain innovation.

  • Fiat-backed stablecoins bring stability and ease of use.
  • Crypto-collateralized ones offer transparency and decentralization.
  • Algorithmic models push innovation but carry higher risks.
  • Commodity-backed coins provide a hedge against inflation and diversify exposure.

Choosing the right type depends on your risk tolerance, use case, and trust level. Whether for trading, saving, or participating in DeFi, understanding the types of stablecoins can help you navigate the crypto ecosystem with confidence.

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APIs are the connective tissue of modern software: they expose functionality, move data, and enable integrations across services, devices, and platforms. A well-designed web API shapes developer experience, system resilience, and operational cost. This article breaks down core concepts, common architectures, security and observability patterns, and practical steps to build and maintain reliable web APIs without assuming a specific platform or vendor.

What is a Web API and why it matters

A web API (Application Programming Interface) is an HTTP-accessible interface that lets clients interact with server-side functionality. APIs can return JSON, XML, or other formats and typically define a contract of endpoints, parameters, authentication requirements, and expected responses. They matter because they enable modularity: front-ends, mobile apps, third-party integrations, and automation tools can all reuse the same backend logic.

When evaluating or designing an API, consider the consumer experience: predictable endpoints, clear error messages, consistent versioning, and comprehensive documentation reduce onboarding friction for integrators. Think of an API as a public product: its usability directly impacts adoption and maintenance burden.

Design patterns and architectures

There are several architectural approaches to web APIs. RESTful (resource-based) design emphasizes nouns and predictable HTTP verbs. GraphQL centralizes query flexibility into a single endpoint and lets clients request only the fields they need. gRPC is used for low-latency, binary RPC between services.

Key design practices:

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  • Keep contracts stable and use semantic versioning or evolving schema techniques (e.g., deprecation headers, feature flags) to handle changes.
  • Document thoroughly using OpenAPI/Swagger, GraphQL schemas, or similar—machine-readable specs enable client generation and automated testing.

Choose the pattern that aligns with your performance, flexibility, and developer ergonomics goals, and make that decision explicit in onboarding docs.

Security, authentication, and rate limiting

Security must be built into an API from day one. Common controls include TLS for transport, OAuth 2.0 / OpenID Connect for delegated authorization, API keys for service-to-service access, and fine-grained scopes for least-privilege access. Input validation, output encoding, and strict CORS policies guard against common injection and cross-origin attacks.

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Performance, monitoring, and testing

Performance considerations span latency, throughput, and resource efficiency. Use caching (HTTP cache headers, CDN, or in-memory caches) to reduce load on origin services. Employ pagination, partial responses, and batch endpoints to avoid overfetching. Instrumentation is essential: traces, metrics, and logs help correlate symptoms, identify bottlenecks, and measure SLAs.

Testing should be layered: unit tests for business logic, contract tests against API schemas, integration tests for end-to-end behavior, and load tests that emulate real-world usage. Observability tools and APMs provide continuous insight; AI-driven analytics platforms such as Token Metrics can help surface unusual usage patterns and prioritize performance fixes based on impact.

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What is the difference between REST and GraphQL?

REST exposes multiple endpoints that represent resources and rely on HTTP verbs for operations. It is simple and maps well to HTTP semantics. GraphQL exposes a single endpoint where clients request precisely the fields they need, which reduces overfetching and can simplify mobile consumption. GraphQL adds complexity in query planning and caching; choose based on client needs and team expertise.

How should I approach API versioning?

Prefer backward-compatible changes over breaking changes. Use semantic versioning for major releases, and consider header-based versioning or URI version prefixes when breaking changes are unavoidable. Maintain deprecation schedules and communicate timelines in documentation and response headers so clients can migrate predictably.

Which authentication method is best for my API?

OAuth 2.0 and OpenID Connect are standard for delegated access and single-sign-on. For machine-to-machine communication, use short-lived tokens issued by a trusted authorization server. API keys can be simple to implement but should be scoped, rotated regularly, and never embedded in public clients without additional protections.

How do I test and monitor an API in production?

Implement synthetic monitoring for critical endpoints, collect real-user metrics (latency percentiles, error rates), and instrument distributed tracing to follow requests across services. Run scheduled contract tests against staging and production-like environments, and correlate incidents with deployment timelines and dependency health.

How do I design for backward compatibility?

Make additive, non-breaking changes where possible: add new fields rather than changing existing ones, and preserve default behaviors. Document deprecated fields and provide feature flags to gate new behavior. Maintain versioned client libraries to give consumers time to upgrade.

Disclaimer

This article is educational and technical in nature. It does not provide legal, financial, or investment advice. Implementations should be evaluated with respect to security policies, compliance requirements, and operational constraints specific to your organization.

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APIs power modern software by exposing discrete access points called endpoints. Whether you re integrating a third-party data feed, building a microservice architecture, or wiring a WebSocket stream, understanding what an api endpoint is and how to design, secure, and monitor one is essential for robust systems.

What is an API endpoint and how it works

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Key technical elements of an endpoint include:

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  • Rate limiting and throttling rules

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Types of endpoints and common protocols

Different application needs favor different endpoint types and protocols:

  • REST endpoints (HTTP/HTTPS): Simple, stateless, and cache-friendly, ideal for resource CRUD operations and broad compatibility.
  • GraphQL endpoints: A single endpoint that accepts queries allowing clients to request exactly the fields they need; reduces overfetching but requires careful schema design and complexity control.
  • WebSocket endpoints: Bidirectional, low-latency channels for streaming updates (market data, notifications). Useful when real-time throughput matters.
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Choosing a protocol depends on consistency requirements, latency tolerance, and client diversity. Hybrid architectures often combine REST for configuration and GraphQL/WebSocket for dynamic data.

Design best practices for robust API endpoints

Good endpoint design improves developer experience and system resilience. Follow these practical practices:

  1. Clear and consistent naming: Use predictable URI patterns and resource-oriented paths. Avoid action-based endpoints like /getUserData in favor of /users/{id}.
  2. Versioning: Expose versioned endpoints (e.g., /v1/users) to avoid breaking changes for consumers.
  3. Input validation: Validate payloads early and return explicit error codes and messages to guide client correction.
  4. Pagination and filtering: For list-heavy endpoints, require pagination tokens or limits to protect backend resources.
  5. Documentation and examples: Provide schema samples, curl examples, and expected response bodies to accelerate integration.

API schema tools (OpenAPI/Swagger, AsyncAPI) let you define endpoints, types, and contracts programmatically, enabling automated client generation, testing, and mock servers during development.

Security, rate limits, and monitoring

Endpoints are primary attack surfaces. Security and observability are critical:

  • Authentication & Authorization: Prefer token-based schemes (OAuth2, JWT) with granular scopes. Enforce least privilege for each endpoint.
  • Transport security: Enforce TLS, HSTS, and secure ciphers to protect data in transit.
  • Rate limiting & quotas: Apply per-key and per-IP limits to mitigate abuse and preserve quality of service.
  • Input sanitization: Prevent injection attacks by whitelisting allowed fields and escaping inputs.
  • Observability: Emit structured logs, traces, and metrics per endpoint. Monitor latency percentiles, error rates, and traffic patterns to detect regressions early.

Operational tooling such as API gateways, service meshes, and managed API platforms provide built-in policy enforcement for security and rate limiting, reducing custom code complexity.

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What is the difference between an api endpoint and an API?

An API is the overall contract and set of capabilities a service exposes; an api endpoint is a specific network address (URI) where one of those capabilities is accessible. Think of the API as the menu and endpoints as the individual dishes.

How should I secure a public api endpoint?

Use HTTPS only, require authenticated tokens with appropriate scopes, implement rate limits and IP reputation checks, and validate all input. Employ monitoring to detect anomalous traffic patterns and rotate credentials periodically.

When should I version my endpoints?

Introduce explicit versioning when you plan to make breaking changes to request/response formats or behavior. Semantic versioning in the path (e.g., /v1/) is common and avoids forcing clients to adapt unexpectedly.

What are effective rate-limiting strategies?

Combine per-key quotas, sliding-window or token-bucket algorithms, and burst allowances. Communicate limits via response headers and provide clear error codes and retry-after values so clients can back off gracefully.

Which metrics should I monitor for endpoints?

Track request rate (RPS), error rate (4xx/5xx), latency percentiles (p50, p95, p99), and active connections for streaming endpoints. Correlate with upstream/downstream service metrics to identify root causes.

When is GraphQL preferable to REST for endpoints?

Choose GraphQL when clients require flexible field selection and you want to reduce overfetching. Prefer REST for simple resource CRUD patterns and when caching intermediaries are important. Consider team familiarity and tooling ecosystem as well.

Disclaimer

The information in this article is technical and educational in nature. It is not financial, legal, or investment advice. Implementations should be validated in your environment and reviewed for security and compliance obligations specific to your organization.

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Modern web and mobile apps exchange data constantly. At the center of that exchange is the REST API — a widely adopted architectural style that standardizes how clients and servers communicate over HTTP. Whether you are a developer, product manager, or researcher, understanding what a REST API is and how it works is essential for designing scalable systems and integrating services efficiently.

What is a REST API? Core principles

A REST API (Representational State Transfer Application Programming Interface) is a style for designing networked applications. It defines a set of constraints that, when followed, enable predictable, scalable, and loosely coupled interactions between clients (browsers, mobile apps, services) and servers. REST is not a protocol or standard; it is a set of architectural principles introduced by Roy Fielding in 2000.

Key principles include:

  • Statelessness: Each request from the client contains all information needed; the server does not store client session state between requests.
  • Resource orientation: Everything is modeled as a resource (users, orders, posts), each identified by a URI (Uniform Resource Identifier).
  • Uniform interface: A standard set of operations (typically HTTP methods) operate on resources in predictable ways.
  • Client-server separation: Clients and servers can evolve independently as long as the interface contract is maintained.
  • Cacheability: Responses can be labeled cacheable or non-cacheable to improve performance and scalability.

How REST APIs work: HTTP methods, status codes, and endpoints

A REST API organizes functionality around resources and uses standard HTTP verbs to manipulate them. Common conventions are:

  • GET — retrieve a resource or list of resources.
  • POST — create a new resource under a collection.
  • PUT — replace an existing resource or create if absent (idempotent).
  • PATCH — apply partial updates to a resource.
  • DELETE — remove a resource.

Responses use HTTP status codes to indicate result state (200 OK, 201 Created, 204 No Content, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error). Payloads are typically JSON but can be XML or other formats. Endpoints are structured hierarchically, for example: /api/users to list users, /api/users/123 to operate on user with ID 123.

Design patterns and best practices for reliable APIs

Designing a robust REST API involves more than choosing verbs and URIs. Adopt patterns that make APIs understandable, maintainable, and secure:

  • Consistent naming: Use plural resource names (/products, /orders), and keep endpoints predictable.
  • Versioning: Expose versions (e.g., /v1/) to avoid breaking clients when changing the contract.
  • Pagination and filtering: For large collections, support parameters for page size, cursors, and search filters to avoid large responses.
  • Error handling: Return structured error responses with codes and human-readable messages to help client debugging.
  • Rate limiting and throttling: Protect backends by limiting request rates and providing informative headers.
  • Security: Use TLS, authenticate requests (OAuth, API keys), and apply authorization checks per resource.

Following these practices improves interoperability and reduces operational risk.

Use cases, tools, and how to test REST APIs

REST APIs are used across web services, microservices, mobile backends, IoT devices, and third-party integrations. Developers commonly use tools and practices to build and validate APIs:

  • API specifications: OpenAPI (formerly Swagger) describes endpoints, parameters, responses, and can be used to generate client/server code and documentation.
  • Testing tools: Postman, curl, and automated test frameworks (JUnit, pytest) validate behavior, performance, and regression checks.
  • Monitoring and observability: Logs, distributed tracing, and metrics (latency, error rates) help identify issues in production.
  • Client SDKs and code generation: Generate typed clients for multiple languages to reduce integration friction.

AI-driven platforms and analytics can speed research and debugging by surfacing usage patterns, anomalies, and integration opportunities. For example, Token Metrics can be used to analyze API-driven data feeds and incorporate on-chain signals into application decision layers without manual data wrangling.

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FAQ: What is REST API — common questions

What is the difference between REST and RESTful?

"REST" refers to the architectural constraints described by Roy Fielding; "RESTful" is a colloquial adjective meaning an API that follows REST principles. Not all APIs labeled RESTful implement every REST constraint strictly.

How does REST compare to SOAP and GraphQL?

SOAP is a protocol with rigid standards and built-in operations (often used in enterprise systems). GraphQL exposes a single endpoint and lets clients request precise data shapes. REST uses multiple endpoints and standard HTTP verbs. Each approach has trade-offs in flexibility, caching, and tooling.

When should I version my REST API?

Version your API before making breaking changes to request/response formats or behavior that existing clients depend on. Common strategies include URI versioning (e.g., /v1/) or header-based versioning.

Are REST APIs secure by default?

No. Security must be designed in: use HTTPS/TLS, authenticate requests, validate input, apply authorization checks, and limit rate to reduce abuse. Treat REST APIs like any other public interface that requires protection.

How do I test and document a REST API effectively?

Use API specifications (OpenAPI) to auto-generate docs and client stubs. Combine manual testing tools like Postman with automated integration and contract tests in CI pipelines to ensure consistent behavior across releases.

Can REST APIs handle streaming or real-time data?

REST is request/response oriented and not ideal for continuous real-time streams. For streaming, consider WebSockets, Server-Sent Events (SSE), or specialized protocols; REST can still be used for control operations and fallbacks.

Disclaimer: This article is educational and technical in nature. It does not provide investment or legal advice. The information is intended to explain REST API concepts and best practices, not to recommend specific products or actions.

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