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s3-lambda VS Edgegap

Compare s3-lambda VS Edgegap and see what are their differences

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s3-lambda logo s3-lambda

Lambda functions over S3 objects: each, map, reduce, filter

Edgegap logo Edgegap

Get your multiplayer game online, worldwide, in minutes with Edgegap’s automated game server hosting & orchestration.
  • s3-lambda Landing page
    Landing page //
    2022-11-04
  • Edgegap Edgegap - Game Server Hosting Orchestration
    Edgegap - Game Server Hosting Orchestration //
    2025-04-30
  • Edgegap Game Server Hosting, Solved
    Game Server Hosting, Solved //
    2025-04-30
  • Edgegap Fully Managed Game Server Hosting
    Fully Managed Game Server Hosting //
    2025-04-30
  • Edgegap Orchestration Performance
    Orchestration Performance //
    2025-04-30
  • Edgegap Pricing - No Wasted Capacity
    Pricing - No Wasted Capacity //
    2025-04-30
  • Edgegap Cross-Platform Game Servers
    Cross-Platform Game Servers //
    2025-04-30
  • Edgegap Edgegap Clients
    Edgegap Clients //
    2025-04-30

Game server hosting, solved.

Edgegap's game server orchestration & managed infrastructure helps all game developers deliver a flawless online multiplayer experience.

Easy to integrate & compatible with major engines including Unreal and Unity and game servers such as Epic Online Services, Photon, Heroic Labs' Nakama, PlayFab, Mirror Networkworking, Fish-Networking, and more.

Proven to scale to 14M CCU for the biggest of launches, and with on-demand deployments to 615+ global locations that delivers 58% average latency reduction vs public cloud. Pay only when players play with our usage-based pricing that helps you avoid overpaying for wasted capacity.

s3-lambda

Website
github.com
Pricing URL
-
$ Details
-
Release Date
-

Edgegap

$ Details
freemium
Release Date
2018 November
Startup details
Country
Canada
State
Quebec
Founder(s)
Mathieu Duperré
Employees
10 - 19

s3-lambda features and specs

  • Batch processing of S3 objects
    s3-lambda provides a straightforward way to perform batch operations on large numbers of S3 objects, enabling map, filter, and reduce-style processing over entire S3 buckets or prefixes without writing boilerplate code.
  • Familiar functional API
    The library uses a functional programming paradigm with operations like map, filter, and reduce, making it intuitive for JavaScript developers to process S3 objects using patterns they already know.
  • Built-in concurrency control
    s3-lambda handles parallel processing of S3 objects with configurable concurrency, allowing users to control how many operations run simultaneously and avoid overwhelming AWS resources or hitting rate limits.
  • Context-aware operations
    The library provides a context object within each operation that includes useful metadata about the current object being processed, simplifying access to S3 object properties during transformations.
  • Easy integration with Lambda
    Designed to work seamlessly within AWS Lambda functions, making it straightforward to set up event-driven, serverless pipelines for processing large volumes of S3 data without managing infrastructure.

Possible disadvantages of s3-lambda

  • Unmaintained project
    The repository appears to be no longer actively maintained, with limited recent commits and unresolved issues, which raises concerns about long-term reliability, security patches, and compatibility with newer AWS SDK versions.
  • Limited documentation
    The project's documentation is relatively sparse, lacking comprehensive examples, edge case handling guidance, and detailed API references, which can make it challenging for new users to adopt effectively.
  • AWS SDK version dependency
    The library depends on an older version of the AWS SDK for JavaScript, which may conflict with projects using the newer AWS SDK v3 and could miss out on performance improvements and features in updated SDKs.
  • Limited error handling flexibility
    The built-in error handling mechanisms are relatively basic, and handling partial failures or implementing sophisticated retry logic for individual object operations requires additional custom code from the developer.
  • Narrow scope of functionality
    The library is tightly focused on S3 object processing and does not integrate with other AWS services or provide utilities beyond basic map/filter/reduce operations, limiting its usefulness in more complex data pipeline scenarios.

Edgegap features and specs

  • Game Server Hosting & Orchestration
    Get your game online in minutes & easily maintain it with optimal performance with game server hosting on the world's largest edge network.
  • Bare Metal Orchestration
    For games with predictable player base, Edgegap’s hybrid game server orchestration leverages bare metal & cloud servers to optimize cost savings.
  • Relays
    Overcome every shortcoming of peer-to-peer networking with Edgegap's network of relays on the world's largest distributed network.
  • Matchmaking
    Edgegap's matchmaking system is fully-managed, infinitely customizable to optimally group players worldwide.
  • Fleet Manager
    Edgegap’s Smart Fleets automatically optimize fleet locations to minimize infrastructure usage, while also reducing latency by an average of 58%, thanks to Edgegap's orchestration.
  • Session Manager
    For games with persistent instances such as massively multiplayer open-worlds, social casuals & COOP, simplify your development process with our Sessions’ built-in ability to create matches/games within a single deployment instance.

Analysis of s3-lambda

Overall verdict

  • s3-lambda is a useful Node.js library for performing operations like map, reduce, and filter directly on S3 objects using Lambda, making it good for developers who need efficient, serverless-based batch processing of S3 data without managing infrastructure. It is well suited for smaller to medium projects but may not be actively maintained for enterprise-scale needs.

Why this product is good

  • Simplifies common S3 batch operations (map, filter, reduce) with a clean, functional API
  • Leverages AWS Lambda for scalable, serverless parallel processing of S3 objects
  • Reduces boilerplate code for iterating over and transforming large numbers of S3 objects
  • Open-source and free to use, allowing customization for specific workflows
  • Integrates well with existing AWS infrastructure and Node.js applications

Recommended for

  • Developers building serverless data pipelines on AWS
  • Teams needing to process or transform large sets of S3 objects without provisioning servers
  • Node.js developers looking for a functional programming approach to S3 operations
  • Projects with batch processing needs that fit within Lambda's execution limits
  • Prototyping or small-to-medium scale ETL tasks involving S3 data

Analysis of Edgegap

Overall verdict

  • Edgegap is a solid choice for game developers and real-time application teams needing global, low-latency multiplayer infrastructure without managing their own server fleets. It offers a distributed edge computing network with dynamic scaling, making it particularly appealing for studios that want to reduce latency for players worldwide while avoiding the complexity of traditional cloud deployment.

Why this product is good

  • Provides a globally distributed edge network that reduces latency for multiplayer and real-time applications
  • Offers automatic and dynamic server scaling based on player demand, avoiding over- or under-provisioning
  • Simplifies deployment with containerized game server hosting, reducing DevOps overhead
  • Pay-as-you-go pricing model can be cost-effective compared to maintaining dedicated servers
  • Integrates with popular game engines and matchmaking systems, easing adoption for developers
  • Strong focus specifically on gaming and real-time use cases rather than generic cloud hosting

Recommended for

  • Indie and mid-sized game studios needing multiplayer infrastructure without dedicated DevOps teams
  • Game developers prioritizing low-latency global player experiences
  • Teams looking for scalable, on-demand server deployment rather than fixed capacity
  • Companies building real-time applications beyond gaming, such as simulations or interactive experiences
  • Developers who want container-based deployment flexibility across multiple cloud providers and regions

s3-lambda videos

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Add video

Edgegap videos

How to add Matchmaking to Unity/Unreal Multiplayer Game with Automated, No-Code Matchmaker

More videos:

  • Tutorial - Add dedicated servers to Unreal Engine multiplayers games without having to build Unreal from Source
  • Tutorial - Add dedicated game servers to Web multiplayer games (Unity Engine)
  • Tutorial - Add dedicated servers to any Unity multiplayer game

Category Popularity

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Cloud Infrastructure
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Databases
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Gaming
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Questions & Answers

As answered by people managing s3-lambda and Edgegap.

What makes your product unique?

Edgegap's answer:

Edgegap orchestrates the world's largest edge network to deploy, on demand, your game server to 615+ locations worldwide. Which directly reduces latency of your multiplayer by 58% on average. It scales with your game's success, up to 14M CCU in 60 minutes. Best of all, it innovative "pay-per-use" means you only pay when players play your game - ensuring you never pay for wasted capacity during development or as your playerbase fluctuates.

How would you describe the primary audience of your product?

Edgegap's answer:

Multiplayer game developers seeking a convenient, powerful and cost-effective solution for authoritative servers ("dedicated servers") hosting & orchestration, relays, or the world's first matchmaking system with latency-based rules.

What's the story behind your product?

Edgegap's answer:

As someone with 20 years of telecom experience, Mathieu Duperré had seen countless industry trends come and go – but edge computing felt different. He saw its bold approach to latency reduction as the next frontier in gaming tech, so he pitched his employer to explore it further.

They humored him initially, but within a few months, the initiative was canned. The company didn’t feel that the gaming market was large or promising enough. Fortunately, their skepticism didn’t deter Mathieu. He knew he had lightning in a bottle, so there was only one thing left to do: quit his long-standing corporate gig to follow his passion.

The first order of business was to research industry conferences. One event in Berlin looked promising, but he was going completely out-of-pocket with zero funding and no product. It was both pricey and risky, with a ton of downside and a shred of potential upside. To earn a free pass, Mathieu jumped on the opportunity to join the event’s hackathon.

Within two weeks, he was onstage in front of the biggest names in the game, presenting the prototype he had pulled out of thin air.

The result? First prize.

Mathieu was immediately swarmed by execs asking to test his product, which didn’t exist yet. Upon touching down in Montreal, he got straight to work renting a small office, hiring 2 engineers for a prototype and started plugging away.

One year later, they had landed a seed round.

Now, more than 5 years later, the team is composed of various departments and colleagues, building the future of edge computing infrastructure!

Which are the primary technologies used for building your product?

Edgegap's answer:

Kubernetes, K8, containers, Docker, container d, container-d, and much more

Who are some of the biggest customers of your product?

Edgegap's answer:

Starbreeze AB (PAYDAY 3), Halfbrick Studios (Thrill of the Fight 2), The Fun Pimps (7 Days to Die: Blood Moon), Mirai Labs (Pegaxy: Blaze), Aether Studios (Rivals of Aether 2), Highwire Games (Six Days in Fallujah), Squido Studios (DigiGods), Blue Duck Studios (Gravity League), HIBER (Hiberworld, Hiber3D) & many more unnanounced studios & games.

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