Enterprise SDK Generation Platform

liblab vs Fern:
Enterprise SDK Generation
Platform Comparison (2025)

See how liblab's enterprise-grade SDK generation platform stacks up against Fern with our detailed feature comparison, security compliance, and proven success metrics.

Enterprise Security

The only SOC2 compliant SDK platform trusted by industry leaders

Superior Developer Experience

Hand-written quality SDKs with comprehensive IntelliSense support

Comprehensive Documentation

Auto-generated code snippets and enhanced OpenAPI specifications

TL;DR how do liblab and Fern differ?

Choosing the right SDK generation tool can significantly impact the speed and ease of your API integrations. liblab and Fern both generate SDKs from OpenAPI specs, but they cater to different needs.

When deciding between liblab and Fern, it largely depends on the balance between developer experience, ease of integration, and flexibility. If you're looking for a more streamlined, developer-friendly experience with comprehensive features, liblab is often the better choice. It provides automated documentation generation, cleaner code, better support for multiple programming languages, and seamless CI/CD integration.

With liblab, you get:

✅ Fully automated, version-controlled documentation with ready-to-use code examples
✅ Strong multi-language support with advanced features for all languages
✅ Modular, clean code architecture that follows best practices for maintainability
✅ Easy CI/CD integration with GitHub Actions, GitLab, Jenkins, and more
✅ Consistent and detailed testing support, including Dev Container support

With Fern, you get:

❌ Limited language support, with advanced features primarily available for Python and TypeScript
❌ SDK documentation embedded within the code, requiring extra effort to extract and use examples
❌ A more complex setup with additional steps for SDK generation and testing
❌ Vendor lock-in with the documentation hosting service

This article compares liblab and Fern from a developer-first perspective, focusing on factors like documentation, ease of use, code quality, and overall developer experience.

Supported Programming Languages

Both liblab and Fern support a wide range of programming languages for SDK generation. However, there are important differences in consistency and feature availability across those languages.

liblab provides robust, feature-complete support across all its supported languages. Every language benefits from a consistent developer experience, including full customization options, complete documentation generation, and all pro features. Fern, on the other hand, officially supports multiple languages, but many of its features are only available in Python and TypeScript.

Language	liblab	Fern
TypeScript
Python
Java
Kotlin
Go
C# / .NET
PHP
Ruby

Feature Support by Language

While both liblab and Fern support a broad set of SDK capabilities, liblab provides more consistent, full-featured support across all programming languages. In contrast, Fern's advanced features are concentrated in TypeScript and Python, often leaving other languages behind.

The table below shows which features are supported by language and platform. liblab's consistent multi-language support suits teams working across multiple ecosystems better.

Feature	liblab	Fern
Registry Publishing (auto-publish to NPM, PyPI, etc.)	✅ All languages	TypeScript, Python, Java
Retries with Backoff (centralized + in-code)	✅ All languages	TypeScript, Python, Java, Go
Code Snippets	✅ All languages	TypeScript, Python
Augment with Custom Code	✅ All languages	TypeScript, Python, Java, Go
Dev Container Support	✅ All languages	❌ Not supported
Auto-Pagination	TypeScript, Python, Java	TypeScript, Python
OAuth Token Refresh	Python, C#, Go	TypeScript, Python, Java
Server-Sent Events / Streaming	TypeScript, Java/Kotlin, Python	TypeScript, Python
Environment Support (multi-env configs)	✅ All	✅ All
Environment Variables	TypeScript, Python, Go	TypeScript, Python, Java
Response Headers	Java/Kotlin, Go	Java
Workflows (combine multiple API steps)	Python	❌ Not supported
Webhook Signature Verification	✅ All	❌ Not supported
Idempotency Headers	✅ All	❌ Not supported
Model Context Protocol	Coming soon	Supported (no language info)
Documentation Generation	✅ All	Only API Reference documentation
Authentication Config	✅ All	✅ All
Merge Multiple APIs	✅	✅

Spec Support

liblab and Fern differ in the specs they can support:

Spec Coverage	liblab	Fern
OpenAPI Versions	OpenAPI 2.0 (Swagger), 3.0, and 3.1	OpenAPI 3.0 and 3.1
Postman Collections	✅	❌
Fern Definition	❌	✅

Both tools can generate SDKs from OpenAPI 3.0 and 3.1 and handle complex specifications like discriminated unions and SSE. liblab also supports common formats like OpenAPI 2.0 (Swagger) and Postman Collections while Fern does not.

Fern does support its own proprietary API specification format known as the Fern Definition. However, since this format is not widely adopted. Relying on a proprietary definition can introduce vendor lock-in and create inflexible dependencies on Fern for SDK generation.

Developer Experience

The developer experience is critical when choosing an SDK generation platform. A seamless, intuitive experience can drastically speed up integration time and reduce friction.

Aspect	liblab	Fern
CLI Setup & Configuration	Streamlined, interactive, single command for SDK generation and testing.	Multiple commands, less continuous flow.
SDK Code Quality	Strong separation of concerns, modular, follows best practices.	Weak separation of concerns, less modular, external dependencies.
Real World Examples	Pre-configured example scripts. Dev Container support.	Requires manual setup, no pre-configured examples.
Documentation	Auto-generated, comprehensive, version-controlled.	Embedded in code, lacks external documentation generation.

CLI Experience

liblab provides a streamlined and interactive CLI setup process. Running the liblab init command guides users in specifying the OpenAPI file and selecting programming languages for SDK generation. This command also facilitates SDK creation and OpenAPI spec validation in a continuous flow.

liblab init

Location of your API specification file (Press Enter to use our sample spec) 
? Select languages for SDK generation  Python,  TypeScript
? Please enter your project name Bookstore
? Select the project licence  MIT
Successfully created liblab.config.json file.
? Do you want to build the SDK now? Yes

✓ No issues detected in the liblab config file.

No hooks found, SDKs will be generated without hooks.

✓ Validation succeeded
Your SDKs are being generated. 
✓ Python built
✓ TypeScript built
✓ Generate package-lock.json for TypeScript
Successfully generated SDKs for Python, TypeScript. ♡

Additionally, liblab makes it easy to update your configuration without editing the JSON file manually. Using the liblab config command, you can retrieve and modify any setting within the liblab.config.json file directly from the CLI. This command-line interface allows for faster iteration, enables easy automation in scripts, and ensures your configuration stays consistent across environments, making it especially useful in CI/CD pipelines.

Fern conducts the SDK generation process via CLI but relies on tags to perform specific actions. The process is less continuous, requiring users to run different commands for configuration and generation after project initiation.

SDK Code Quality

Clean, modular code isn't just a preference, it's a necessity for teams that need to use, extend, or audit your SDKs. Whether it's a product engineer integrating with your API or a developer working under a deadline, clean and intuitive SDKs can dramatically reduce friction.

liblab-generated SDKs follow object-oriented best practices and maintain a clean, modular architecture. The code is structured into distinct files and folders, with clear separation between models, services, utilities, and core logic. Models are defined as classes with explicit enums, type safety, and validation logic that mirrors hand-written code.

liblab SDKs feel like they were written by a developer for other developers, without boilerplate, excessive nesting, or cryptic wrappers.

Fern's generated SDKs follow a less modular approach. Much of the business logic is split across the project, and models often rely on external third party libraries.

Feature	liblab	Fern
Model Type Safety	✅ Uses Union, enums, and strict typing for better compile-time checks	❌ Relies on basic type hints and casting.
Error Handling	✅ Custom error classes with specific exception handling per case	❌ Generic ApiError handling without specific cases
Type Validation	✅ Automatic with custom decorators	❌ Manual or external (Pydantic)
End-user Readability	✅ Reads like native code	❌ Feels autogenerated
Inline Docs & Docstrings	✅ Included	❌ Sparse or generic

The code snippets below show how the same service is implemented in SDKs generated by liblab and Fern, using the Bookstore API as an example. You can compare the differences for yourself below.

python

# This file was generated by liblab | https://liblab.com/

from __future__ import annotations
from enum import Enum
from typing import Union
from typing import List
from .utils.json_map import JsonMap
from .utils.base_model import BaseModel
from .utils.one_of_base_model import OneOfBaseModel
from .user import User
from .fantasy_book import FantasyBook
from .programming_book import ProgrammingBook
from .sci_fi_book import SciFiBook


class Status(Enum):
    """An enumeration representing different categories.

    :cvar PENDING: "pending"
    :vartype PENDING: str
    :cvar SHIPPED: "shipped"
    :vartype SHIPPED: str
    :cvar DELIVERED: "delivered"
    :vartype DELIVERED: str
    """

    PENDING = "pending"
    SHIPPED = "shipped"
    DELIVERED = "delivered"

    def list():
        """Lists all category values.

        :return: A list of all category values.
        :rtype: list
        """
        return list(map(lambda x: x.value, Status._member_map_.values()))


class ProductsGuard(OneOfBaseModel):
    class_list = {
        "FantasyBook": FantasyBook,
        "ProgrammingBook": ProgrammingBook,
        "SciFiBook": SciFiBook,
    }


Products = Union[FantasyBook, ProgrammingBook, SciFiBook]


@JsonMap({"id_": "id", "date_": "date"})
class Order(BaseModel):
    """Order

    :param id_: id_
    :type id_: int
    :param date_: date_
    :type date_: str
    :param status: status
    :type status: Status
    :param user: user
    :type user: User
    :param products: products
    :type products: List[Products]
    """

    def __init__(
        self,
        id_: int,
        date_: str,
        status: Status,
        user: User,
        products: List[Products],
        **kwargs,
    ):
        """Order

        :param id_: id_
        :type id_: int
        :param date_: date_
        :type date_: str
        :param status: status
        :type status: Status
        :param user: user
        :type user: User
        :param products: products
        :type products: List[Products]
        """
        self.id_ = id_
        self.date_ = date_
        self.status = self._enum_matching(status, Status.list(), "status")
        self.user = self._define_object(user, User)
        self.products = self._define_list(products, Products)
        self._kwargs = kwargs

Fern
# MIT Licensed
# This file was auto-generated by Fern from our API Definition.

import typing
from ..core.client_wrapper import SyncClientWrapper
from ..core.request_options import RequestOptions
from ..types.order import Order
from ..core.pydantic_utilities import parse_obj_as
from json.decoder import JSONDecodeError
from ..core.api_error import ApiError
from ..types.user_id import UserId
from ..types.product_id import ProductId
from ..core.jsonable_encoder import jsonable_encoder
from ..core.client_wrapper import AsyncClientWrapper

# this is used as the default value for optional parameters
OMIT = typing.cast(typing.Any, ...)


class OrdersClient:
    def __init__(self, *, client_wrapper: SyncClientWrapper):
        self._client_wrapper = client_wrapper

    def get_all_orders(self, *, request_options: typing.Optional[RequestOptions] = None) -> typing.List[Order]:
        """
        Returns a list of orders

        Parameters
        ----------
        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        typing.List[Order]
            A list of orders

        Examples
        --------
        from test import TestApi

        client = TestApi(
            api_key="YOUR_API_KEY",
        )
        client.orders.get_all_orders()
        """
        _response = self._client_wrapper.httpx_client.request(
            "orders",
            method="GET",
            request_options=request_options,
        )
        try:
            if 200 <= _response.status_code < 300:
                return typing.cast(
                    typing.List[Order],
                    parse_obj_as(
                        type_=typing.List[Order],  # type: ignore
                        object_=_response.json(),
                    ),
                )
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

    def create_order(
        self,
        *,
        user: UserId,
        products: typing.Sequence[ProductId],
        request_options: typing.Optional[RequestOptions] = None,
    ) -> Order:
        """
        Creates a new order

        Parameters
        ----------
        user : UserId

        products : typing.Sequence[ProductId]

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        Order
            Order created successfully

        Examples
        --------
        from test import TestApi

        client = TestApi(
            api_key="YOUR_API_KEY",
        )
        client.orders.create_order(
            user=1,
            products=[1, 3],
        )
        """
        _response = self._client_wrapper.httpx_client.request(
            "orders",
            method="POST",
            json={
                "user": user,
                "products": products,
            },
            headers={
                "content-type": "application/json",
            },
            request_options=request_options,
            omit=OMIT,
        )
        try:
            if 200 <= _response.status_code < 300:
                return typing.cast(
                    Order,
                    parse_obj_as(
                        type_=Order,  # type: ignore
                        object_=_response.json(),
                    ),
                )
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

    def get_order_by_id(self, order_id: int, *, request_options: typing.Optional[RequestOptions] = None) -> Order:
        """
        Returns a single order

        Parameters
        ----------
        order_id : int
            ID of the order to return

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        Order
            A single order

        Examples
        --------
        from test import TestApi

        client = TestApi(
            api_key="YOUR_API_KEY",
        )
        client.orders.get_order_by_id(
            order_id=1,
        )
        """
        _response = self._client_wrapper.httpx_client.request(
            f"orders/{jsonable_encoder(order_id)}",
            method="GET",
            request_options=request_options,
        )
        try:
            if 200 <= _response.status_code < 300:
                return typing.cast(
                    Order,
                    parse_obj_as(
                        type_=Order,  # type: ignore
                        object_=_response.json(),
                    ),
                )
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

    def get_order_stream(self, *, request_options: typing.Optional[RequestOptions] = None) -> None:
        """
        Returns a stream of orders

        Parameters
        ----------
        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        None

        Examples
        --------
        from test import TestApi

        client = TestApi(
            api_key="YOUR_API_KEY",
        )
        client.orders.get_order_stream()
        """
        _response = self._client_wrapper.httpx_client.request(
            "orderstream",
            method="GET",
            request_options=request_options,
        )
        try:
            if 200 <= _response.status_code < 300:
                return
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)


class AsyncOrdersClient:
    def __init__(self, *, client_wrapper: AsyncClientWrapper):
        self._client_wrapper = client_wrapper

    async def get_all_orders(self, *, request_options: typing.Optional[RequestOptions] = None) -> typing.List[Order]:
        """
        Returns a list of orders

        Parameters
        ----------
        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        typing.List[Order]
            A list of orders

        Examples
        --------
        import asyncio
        from test import AsyncTestApi

        client = AsyncTestApi(
            api_key="YOUR_API_KEY",
        )


        async def main() -> None:
            await client.orders.get_all_orders()


        asyncio.run(main())
        """
        _response = await self._client_wrapper.httpx_client.request(
            "orders",
            method="GET",
            request_options=request_options,
        )
        try:
            if 200 <= _response.status_code < 300:
                return typing.cast(
                    typing.List[Order],
                    parse_obj_as(
                        type_=typing.List[Order],  # type: ignore
                        object_=_response.json(),
                    ),
                )
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

    async def create_order(
        self,
        *,
        user: UserId,
        products: typing.Sequence[ProductId],
        request_options: typing.Optional[RequestOptions] = None,
    ) -> Order:
        """
        Creates a new order

        Parameters
        ----------
        user : UserId

        products : typing.Sequence[ProductId]

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        Order
            Order created successfully

        Examples
        --------
        import asyncio
        from test import AsyncTestApi

        client = AsyncTestApi(
            api_key="YOUR_API_KEY",
        )


        async def main() -> None:
            await client.orders.create_order(
                user=1,
                products=[1, 3],
            )


        asyncio.run(main())
        """
        _response = await self._client_wrapper.httpx_client.request(
            "orders",
            method="POST",
            json={
                "user": user,
                "products": products,
            },
            headers={
                "content-type": "application/json",
            },
            request_options=request_options,
            omit=OMIT,
        )
        try:
            if 200 <= _response.status_code < 300:
                return typing.cast(
                    Order,
                    parse_obj_as(
                        type_=Order,  # type: ignore
                        object_=_response.json(),
                    ),
                )
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

    async def get_order_by_id(self, order_id: int, *, request_options: typing.Optional[RequestOptions] = None) -> Order:
        """
        Returns a single order

        Parameters
        ----------
        order_id : int
            ID of the order to return

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        Order
            A single order

        Examples
        --------
        import asyncio
        from test import AsyncTestApi

        client = AsyncTestApi(
            api_key="YOUR_API_KEY",
        )


        async def main() -> None:
            await client.orders.get_order_by_id(
                order_id=1,
            )


        asyncio.run(main())
        """
        _response = await self._client_wrapper.httpx_client.request(
            f"orders/{jsonable_encoder(order_id)}",
            method="GET",
            request_options=request_options,
        )
        try:
            if 200 <= _response.status_code < 300:
                return typing.cast(
                    Order,
                    parse_obj_as(
                        type_=Order,  # type: ignore
                        object_=_response.json(),
                    ),
                )
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

    async def get_order_stream(self, *, request_options: typing.Optional[RequestOptions] = None) -> None:
        """
        Returns a stream of orders

        Parameters
        ----------
        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        None

        Examples
        --------
        import asyncio
        from test import AsyncTestApi

        client = AsyncTestApi(
            api_key="YOUR_API_KEY",
        )


        async def main() -> None:
            await client.orders.get_order_stream()


        asyncio.run(main())
        """
        _response = await self._client_wrapper.httpx_client.request(
            "orderstream",
            method="GET",
            request_options=request_options,
        )
        try:
            if 200 <= _response.status_code < 300:
                return
            _response_json = _response.json()
        except JSONDecodeError:
            raise ApiError(status_code=_response.status_code, body=_response.text)
        raise ApiError(status_code=_response.status_code, body=_response_json)

Generated Documentation

Clear and accessible documentation is essential for any SDK. A well-structured guide helps developers integrate your API and also ensures they can maintain and extend their use of the SDK over time. Both liblab and Fern provide this documentation but the approach and developer experience differ significantly.

liblab automatically generates complete documentation for every SDK, including clear explanations of how to use the SDK's services and models. This documentation is ready to use immediately after SDK generation. Since it's generated at the same time as the SDK, it's always in sync with the latest version of the code. Additionally, liblab provides fully functional, complete code examples within its documentation. These code snippets are not just theoretical examples but ready-to-use, well-structured blocks of code that developers can copy and paste directly into their projects.

liblab's auto-generated documentation include:

Code examples for all services, making it easy for users to get started and reference correct usage patterns.
A clear, well-organized structure that helps developers find the information they need quickly.
Embeddable SDK code snippets that are automatically generated and can be shared using documentation providers such as ReadMe, Mintlify, Redocly, or Docusaurus.
Version-controlled documentation that updates automatically as your SDK evolves.

In contrast, Fern requires purchase of an additional product to produce SDK documentation. Confusingly, SDK examples are also embedded within Fern's SDK code itself. This approach requires developers to either pay additional fees or let their users search through the SDK codebase to find relevant examples. Furthermore, these examples often lack context, leaving developers to figure out how to import the SDK and handle the response on their own. This can lead to unnecessary friction for new users as they attempt to understand how to integrate the SDK into their projects.

Fern's optional documentation hosting service auto-generates docs with request/response examples and SDK snippets. However, you can only host the documentation on Fern's own documentation service. This dependency further increases vendor lock-in and serves as a significant limitation for teams looking to integrate with their existing documentation portals. In contrast liblab offers the ability to integrate their generated docs with any documentation service that supports OpenAPI specifications or Markdown files such as Redocly, ReadMe.io, Mintlify, and Docusaurus.

Feature	liblab	Fern
Code Example Location	✅ Autogenerated in the SDK documentation	❌ Scattered throughout the SDK code
Completeness of Example	✅ Full example with imports, configuration, API call, and response handling	❌ Partial example, missing SDK imports and response checks
Ease of Use	✅ Ready-to-use code, just copy and paste	❌ Requires extra effort to find, understand, and adapt the example
Documentation Platforms	✅ Supports every major documentation platform	❌ Requires vendor lock-in with Fern's documentation platform

The following code snippets highlight the difference between the generated examples from liblab and Fern. The example from liblab is extracted directly from the autogenerated documentation, providing a clear, ready-to-use code sample. The Fern example below was embedded within the method implementation and comes from the TypeScript file where the methods are defined.

typescript

import { InvoiceQuery, SearchInvoicesRequest, Company } from 'company';

(async () => {
  const company = new Company({
    token: 'YOUR_TOKEN',
  });

  const invoiceFilter: InvoiceFilter = {
    locationIds: ['ES0RJRZYEC39A'],
    customerIds: ['JDKYHBWT1D4F8MFH63DBMEN8Y4'],
  };

  const invoiceSortField = 'INVOICE_SORT_DATE';
  const sortOrder = 'DESC';

  const invoiceSort: InvoiceSort = {
    field: invoiceSortField,
    order: sortOrder,
  };

  const invoiceQuery: InvoiceQuery = {
    filter: invoiceFilter,
    sort: invoiceSort,
  };

  const searchInvoicesRequest: SearchInvoicesRequest = {
    query: invoiceQuery,
    limit: 3,
    cursor: 'cursor',
  };

  const { data } = await company.invoices.searchInvoices(searchInvoicesRequest);

  console.log(data);
})();

Fern
// MIT Licensed
/**
 * Searches for invoices from a location specified in
 * the filter. You can optionally specify customers in the filter for whom to
 * retrieve invoices. In the current implementation, you can only specify one location and
 * optionally one customer.
 *
 * The response is paginated. If truncated, the response includes a `cursor`
 * that you use in a subsequent request to retrieve the next set of invoices.
 *
 * @param {Company.SearchInvoicesRequest} request
 * @param {Invoices.RequestOptions} requestOptions - Request-specific configuration.
 *
 * @example
 *     await client.invoices.search({
 *         query: {
 *             filter: {
 *                 locationIds: ["ES0RJRZYEC39A"],
 *                 customerIds: ["JDKYHBWT1D4F8MFH63DBMEN8Y4"]
 *             },
 *             sort: {
 *                 field: "INVOICE_SORT_DATE",
 *                 order: "DESC"
 *             }
 *         },
 *         limit: 100
 *     })
 */

Testing Generated SDKs

Effective testing of an SDK immediately after its generation can save time during development. The way liblab and Fern handle testing is significantly different.

With liblab, each generated SDK comes with pre-configured example scripts. This allows developers to run a single command to test the SDK against either a local or remote API. This seamless approach to testing ensures that developers can quickly confirm functionality without unnecessary setup or troubleshooting.

Moreover, liblab takes testing a step further by offering sandbox environments for all supported languages using Dev Containers. By leveraging Dev Containers, liblab guarantees that the development environment is consistent and reproducible. Any developer who clones the repository will automatically receive the same setup, eliminating the need for manual configuration and ensuring that the SDK works reliably across different environments.

Fern allows you to generate “preview” versions of your SDKs, which are essentially local copies meant for testing. However, Fern lacks guidance in its official documentation on how to use these locally generated SDKs, and it doesn't automatically generate README files with setup instructions. As a result, getting started with testing the SDKs can be more challenging for users.

While Fern does generate unit tests for SDKs, these tests provide no utility as they're simply testing automatically generated code.

Integration with CI/CD Pipelines

A smooth CI/CD workflow is critical for automating SDK generation and keeping client libraries up to date as your API evolves. liblab offers integration with all major CI/CD platforms:

GitHub Actions
GitLab Pipelines
Jenkins Pipelines
Bitbucket Pipelines

liblab's automation approach means you can get integrated quickly. Its pre-built support for multiple CI/CD platforms ensures SDKs are continuously generated and published without manual effort, keeping them reliable, versioned, and always aligned with your latest API specs.

Fern, by comparison, offers integration only with GitHub and GitLab. You'll need to create your own workflow for CI tools like Jenkins or Bitbucket.

Security Considerations

Security is a critical concern when choosing an SDK generation platform, especially for organizations operating in regulated industries or handling sensitive customer data.

Both liblab and Fern support the core authentication mechanisms you'd expect from modern tools, including:

✅ Authentication configuration supporting Bearer tokens, Basic API keys, and OAuth 2.0
✅ Full OAuth 2.0 flow support
✅ Use of environment variables to manage secrets securely
✅ Custom headers for flexible integration with proprietary auth systems

These features make both platforms capable of supporting a wide variety of standard authentication setups.

However, liblab stands apart as the company is fully SOC 2 certified, meaning it meets rigorous security and data protection standards. This makes liblab a safer and more compliant choice for enterprise teams or companies working in regulated sectors. Fern, on the other hand, does not hold a SOC 2 certification.

Additionally, liblab-generated SDKs are lightweight and have minimal reliance on external libraries, reducing the attack surface and minimizing risks associated with third-party code. Fern's SDKs, however, rely on external libraries. This dependency can introduce additional security and maintenance concerns, especially over time.

Criteria	liblab	Fern
Bearer Token / Basic / OAuth 2.0
Environment Variables
Custom Headers
SOC 2 Compliance
Minimal 3rd Party Libraries

Versioning & Maintenance

API changes are inevitable, and how an SDK generation platform handles versioning can greatly impact your workflow, especially as your API grows more complex.

liblab includes built-in version tracking and history management directly in its dashboard, allowing you to:

Track and revert to previous SDK builds.
Automatically update client libraries as your API evolves.
Manage and distribute multiple SDK versions in parallel.

This centralized versioning system helps teams reduce manual overhead and ensures consistent SDK releases across environments and consumers.

Fern, by contrast, does not maintain a centralized version history or built-in restoration tools. This puts the responsibility of version management entirely on your CI/CD workflows.

Summary

liblab offers a superior SDK generation experience, with a clean, modular architecture and fully automated documentation, including detailed, ready-to-use code examples. Its consistent multi-language support, seamless testing process, and built-in version tracking make it the ideal choice for teams looking for a streamlined, developer-friendly solution.

Fern, while functional, has limitations in language support and documentation. Its multiple points of vendor lock-in make it a hard choice for SDK generation. For teams prioritizing efficiency, scalability, and ease of use, liblab stands out as the better choice in the SDK generation space.