AWS Lambda vs Hazelcast

Overview

AWS Lambda

Stacks26.0K

Followers18.8K

Votes432

Hazelcast

Stacks427

Followers474

Votes59

GitHub Stars6.4K

Forks1.9K

AWS Lambda vs Hazelcast: What are the differences?

Deployment Model: AWS Lambda follows a serverless computing model where the underlying infrastructure is managed by AWS, allowing developers to focus solely on their code, while Hazelcast is designed for use on a cluster of servers, providing a distributed in-memory data grid for high performance and scalability.
Programming Languages: AWS Lambda supports multiple programming languages such as Python, Node.js, Java, and C#, whereas Hazelcast is programmed in Java and provides client APIs for other languages like C++, .NET, and Python for accessing the Hazelcast cluster.
Use Cases: AWS Lambda is commonly used for event-driven applications, real-time file processing, and building serverless architectures, while Hazelcast is used for caching, real-time analytics, messaging, and as a distributed cache to supplement databases.
Scalability: AWS Lambda automatically scales based on the number of incoming requests, allowing developers to pay only for resources used, while Hazelcast can be scaled horizontally by adding more servers to the cluster to increase processing power and storage capacity.
State Management: AWS Lambda is stateless by design, meaning it does not retain information between function executions, whereas Hazelcast provides distributed in-memory storage allowing for stateful operations and data sharing among multiple nodes in the cluster.
Pricing Model: AWS Lambda bills users based on the number of requests and the duration of code execution, with a free tier for low usage, while Hazelcast follows a subscription-based pricing model depending on the features and support level chosen.

In Summary, AWS Lambda and Hazelcast differ in deployment model, supported programming languages, use cases, scalability, state management, and pricing model.

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Advice on AWS Lambda, Hazelcast

Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceon

Heroku

AWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

Developer Experience trumps everything.
AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

Pure, uncut, self hosted Kubernetes — way too much complexity
Managed Kubernetes in various flavors — still too much complexity
Zeit — Maybe, but no Docker support
Elastic Beanstalk — Maybe, bit old but does the job
Heroku
Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

Developer Experience / DX 🤓
Ops Experience / OX 🐂 (?)
Cost 💵
Lock in 🔐

Read the full post linked below for all details

357k views357k

Comments

Mark

Nov 2, 2020

Needs adviceon

Microsoft Azure

Need advice on what platform, systems and tools to use.

Evaluating whether to start a new digital business for which we will need to build a website that handles all traffic. Website only right now. May add smartphone apps later. No desktop app will ever be added. Website to serve various countries and languages. B2B and B2C type customers. Need to handle heavy traffic, be low cost, and scale well.

We are open to either build it on AWS or on Microsoft Azure.

Apologies if I'm leaving out some info. My first post. :) Thanks in advance!

133k views133k

Comments

Detailed Comparison

AWS Lambda	Hazelcast
AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.	With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model	Distributed implementations of java.util.{Queue, Set, List, Map};Distributed implementation of java.util.concurrent.locks.Lock;Distributed implementation of java.util.concurrent.ExecutorService;Distributed MultiMap for one-to-many relationships;Distributed Topic for publish/subscribe messaging;Synchronous (write-through) and asynchronous (write-behind) persistence;Transaction support;Socket level encryption support for secure clusters;Second level cache provider for Hibernate;Monitoring and management of the cluster via JMX;Dynamic HTTP session clustering;Support for cluster info and membership events;Dynamic discovery, scaling, partitioning with backups and fail-over
Statistics
GitHub Stars -	GitHub Stars 6.4K
GitHub Forks -	GitHub Forks 1.9K
Stacks 26.0K	Stacks 427
Followers 18.8K	Followers 474
Votes 432	Votes 59
Pros & Cons
Pros 129 No infrastructure 83 Cheap 70 Quick 59 Stateless 47 No deploy, no server, great sleep Cons 7 Cant execute ruby or go 3 Compute time limited 1 Can't execute PHP w/o significant effort	Pros 11 High Availibility 6 Distributed compute 6 Distributed Locking 5 Sharding 4 Load balancing Cons 4 License needed for SSL
Integrations
No integrations available	Java Spring

What are some alternatives to AWS Lambda, Hazelcast?

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

Related Comparisons

AWS Lambda vs Hazelcast: What are the differences?

Deployment Model: AWS Lambda follows a serverless computing model where the underlying infrastructure is managed by AWS, allowing developers to focus solely on their code, while Hazelcast is designed for use on a cluster of servers, providing a distributed in-memory data grid for high performance and scalability.
Programming Languages: AWS Lambda supports multiple programming languages such as Python, Node.js, Java, and C#, whereas Hazelcast is programmed in Java and provides client APIs for other languages like C++, .NET, and Python for accessing the Hazelcast cluster.
Use Cases: AWS Lambda is commonly used for event-driven applications, real-time file processing, and building serverless architectures, while Hazelcast is used for caching, real-time analytics, messaging, and as a distributed cache to supplement databases.
Scalability: AWS Lambda automatically scales based on the number of incoming requests, allowing developers to pay only for resources used, while Hazelcast can be scaled horizontally by adding more servers to the cluster to increase processing power and storage capacity.
State Management: AWS Lambda is stateless by design, meaning it does not retain information between function executions, whereas Hazelcast provides distributed in-memory storage allowing for stateful operations and data sharing among multiple nodes in the cluster.
Pricing Model: AWS Lambda bills users based on the number of requests and the duration of code execution, with a free tier for low usage, while Hazelcast follows a subscription-based pricing model depending on the features and support level chosen.

In Summary, AWS Lambda and Hazelcast differ in deployment model, supported programming languages, use cases, scalability, state management, and pricing model.

AWS Lambda vs Hazelcast

Overview