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.

Build Smarter Crypto Apps &
AI Agents in Minutes, Not Months
Real-time prices, trading signals, and on-chain insights all from one powerful API.
Grab a Free API Key
Token Metrics Team
Token Metrics Team

Recent Posts

Research

API Management Essentials for Teams

Token Metrics Team
5
MIN

APIs are the connective tissue of modern software. As organizations expose more endpoints to partners, internal teams and third-party developers, effective api management becomes a competitive and operational imperative. This article breaks down practical frameworks, governance guardrails, and monitoring strategies that help teams scale APIs securely and reliably without sacrificing developer velocity.

Overview: What API management solves

API management is the set of practices, tools and processes that enable teams to design, publish, secure, monitor and monetize application programming interfaces. At its core it addresses three recurring challenges: consistent access control, predictable performance, and discoverability for developers. Well-managed APIs reduce friction for consumers, decrease operational incidents, and support governance priorities such as compliance and data protection.

Think of api management as a lifecycle discipline: from design and documentation to runtime enforcement and iterative refinement. Organizations that treat APIs as products—measuring adoption, latency, error rates, and business outcomes—are better positioned to scale integrations without accumulating technical debt.

Governance & Security: Policies that scale

Security and governance are non-negotiable for production APIs. Implement a layered approach:

  • Access control: Use token-based authentication (OAuth 2.0, JWT) and centralize identity validation at the gateway to avoid duplicating logic across services.
  • Rate limiting & quotas: Protect backend services and control cost by enforcing per-key or per-tenant limits. Different tiers can align with SLAs for partners.
  • Input validation & schema contracts: Define explicit contracts using OpenAPI/JSON Schema and validate at the edge to reduce injection and integration errors.
  • Audit & compliance: Log authentication events, data access, and configuration changes. Retain logs in a way that maps to regulatory obligations.

Combining automated policy enforcement at an API gateway with a governance framework (ownerable APIs, review gates, and versioning rules) ensures changes are controlled without slowing legitimate feature delivery.

Developer experience & the API product model

Developer experience (DX) determines adoption. Treat APIs as products by providing clear documentation, SDKs and a self-service developer portal. Key practices include:

  • Interactive docs: Publish OpenAPI-driven docs that allow developers to try endpoints in a sandbox.
  • Onboarding flows: Provide quick start guides, sample payloads and error explanations to reduce time-to-first-call.
  • Versioning strategy: Use semantic versioning and deprecation notices to minimize breaking changes.
  • Feedback loops: Instrument usage and surface developer issues to product owners so APIs evolve with consumer needs.

Metrics to track DX include signups, first successful call time, and repeat usage per key. These are leading indicators of whether an API is fulfilling its product intent.

Monitoring, observability & reliability

Operational visibility is essential for api management. Implement monitoring at multiple layers—gateway, service, and database—to triangulate causes when issues occur. Core telemetry includes:

  • Traffic metrics: requests per second, latency percentiles (p50/p95/p99), and throughput.
  • Error rates: HTTP 4xx/5xx breakdowns, client-specific failure patterns, and circuit-breaker triggers.
  • Business KPIs: API calls tied to revenue, conversions, or key workflows to prioritize fixes that have impact.

Observability practices—distributed tracing, structured logs, and context propagation—help teams move from alert fatigue to actionable incident response. Build runbooks that map common alerts to remediation steps and owners.

Implementation roadmap & tooling choices

Adopt an incremental roadmap rather than a big-bang rollout. A pragmatic sequence looks like:

  1. Inventory existing endpoints and annotate owners.
  2. Standardize contracts with OpenAPI and publish baseline docs.
  3. Introduce an API gateway for auth, rate limiting, and basic WAF rules.
  4. Instrument telemetry, set SLAs, and define retention for logs and traces.
  5. Launch a developer portal and iterate based on usage signals.

Choose tools that match team maturity: managed API platforms accelerate setup for companies lacking infra resources, while open-source gateways provide control for those with specialized needs. Evaluate vendors on extensibility, observability integrations, and policy-as-code support to avoid lock-in.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

What is API management and why does it matter?

API management encompasses the processes and tools required to publish, secure, monitor, and monetize APIs. It matters because it enables predictable, governed access to services while maintaining developer productivity and operational reliability.

Which components make up an API management stack?

Common components include an API gateway (auth, routing, rate limiting), developer portal (docs, keys), analytics and monitoring systems (metrics, traces), and lifecycle tooling (design, versioning, CI/CD integrations).

How should teams approach API security?

Implement defense-in-depth: centralized authentication, token validation, input schema checks, rate limits, and continuous auditing. Shift security left by validating contracts and scanning specs before deployment.

What metrics are most useful for API health?

Track latency percentiles, error rates, traffic patterns, and consumer-specific usage. Pair operational metrics with business KPIs (e.g., API-driven signups) to prioritize work that affects outcomes.

How do teams manage breaking changes?

Use explicit versioning, deprecation windows, and dual-running strategies where consumers migrate incrementally. Communicate changes via the developer portal and automated notifications tied to API keys.

When should an organization introduce an API gateway?

Introduce a gateway early when multiple consumers, partners, or internal teams rely on APIs. A gateway centralizes cross-cutting concerns and reduces duplicated security and routing logic.

Disclaimer

This article is for educational and informational purposes only. It provides neutral, analytical information about api management practices and tools and does not constitute professional or investment advice.

Research

How Modern Web APIs Power Connected Apps

Token Metrics Team
5
MIN

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:

  • Model your resources to reflect domain concepts; avoid ad-hoc endpoints that duplicate behavior.
  • 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.

Operational protections such as rate limiting, quotas, and circuit breakers help preserve availability if a client misbehaves or a downstream dependency degrades. Design your error responses to be informative to developers but avoid leaking internal implementation details. Centralized authentication and centralized secrets management (vaults, KMS) reduce duplication and surface area for compromise.

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.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

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.

Research

API Endpoint Essentials: Design, Security & Tips

Token Metrics Team
5
MIN

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

An api endpoint is a network-accessible URL or address that accepts requests and returns responses according to a protocol (usually HTTP/HTTPS or WebSocket). Conceptually, an endpoint maps a client intent to a server capability: retrieve a resource, submit data, or subscribe to updates. In a RESTful API, endpoints often follow noun-based paths (e.g., /users/123) combined with HTTP verbs (GET, POST, PUT, DELETE) to indicate the operation.

Key technical elements of an endpoint include:

  • URI pattern (path and optional query parameters)
  • Supported methods (verbs) and expected payloads
  • Authentication and authorization requirements
  • Response format and status codes
  • Rate limiting and throttling rules

Endpoints can be public (open to third parties) or private (internal to a service mesh). For crypto-focused data integrations, api endpoints may also expose streaming interfaces (WebSockets) or webhook callbacks for asynchronous events. For example, Token Metrics is an example of an analytics provider that exposes APIs for research workflows.

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.
  • Webhook endpoints: Server-to-server callbacks where your service exposes a publicly accessible endpoint to receive event notifications from another system.

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.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

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.

Choose from Platinum, Gold, and Silver packages
Reach with 25–30% open rates and 0.5–1% CTR
Craft your own custom ad—from banners to tailored copy
Perfect for Crypto Exchanges, SaaS Tools, DeFi, and AI Products