AWS Lambda vs Cassandra

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

AWS Lambda

Stacks26.0K

Followers18.8K

Votes432

AWS Lambda vs Cassandra: What are the differences?

Introduction

When considering cloud computing services, it's important to understand the key differences between AWS Lambda and Cassandra to make informed decisions based on specific requirements and use cases.

Deployment Model: AWS Lambda is a serverless computing service that allows developers to run code without provisioning or managing servers. On the other hand, Cassandra is a distributed database system designed for handling large amounts of data across multiple servers. The key difference lies in the deployment model - Lambda for serverless code execution and Cassandra for distributed data storage.
Computational Focus: AWS Lambda is more focused on executing short-lived functions in response to events, making it ideal for event-driven architectures and microservices. In contrast, Cassandra is a NoSQL database known for its efficient handling of high-velocity, varied data sources, and massive scalability. The difference in computational focus makes Lambda suitable for lightweight, stateless functions and Cassandra for data-intensive applications.
Managed Service: AWS Lambda is a fully managed service provided by Amazon Web Services, which takes care of infrastructure provisioning, scaling, and maintenance. On the other hand, deploying and managing Cassandra clusters require more manual configuration and monitoring efforts by the users. This difference in managed services can impact operational overhead and ease of deployment.
Scaling Behavior: AWS Lambda automatically scales resources based on the incoming request volume, allowing for seamless handling of varying workloads. Cassandra, on the other hand, requires manual configuration and oversight for scaling both horizontally and vertically. The difference lies in the automatic scaling capabilities of Lambda versus the more hands-on approach needed for Cassandra.
Data Structure: AWS Lambda operates on individual functions or tasks, while Cassandra stores data in a schema-free, distributed fashion across a cluster of nodes. This difference in data structure reflects the distinct purposes of the two services - Lambda for processing discrete tasks and Cassandra for storing and querying large volumes of unstructured data efficiently.
Pricing Model: AWS Lambda follows a pay-as-you-go pricing model based on the number of requests and compute time, with no upfront costs or infrastructure fees. In contrast, Cassandra typically involves upfront hardware and deployment costs for setting up clusters, along with ongoing maintenance expenses. The difference in pricing models can affect the cost-effectiveness and budgeting considerations for utilizing either service.

In Summary, understanding the key differences between AWS Lambda and Cassandra can help in selecting the appropriate service based on the specific needs of your applications.

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Advice on Cassandra, AWS Lambda

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

Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

174k views174k

Comments

Detailed Comparison

Cassandra	AWS Lambda
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.	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.
-	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
Statistics
GitHub Stars 9.5K	GitHub Stars -
GitHub Forks 3.8K	GitHub Forks -
Stacks 3.6K	Stacks 26.0K
Followers 3.5K	Followers 18.8K
Votes 507	Votes 432
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Updates 1 Size	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

What are some alternatives to Cassandra, AWS Lambda?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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AWS Lambda vs Cassandra: What are the differences?

Introduction

When considering cloud computing services, it's important to understand the key differences between AWS Lambda and Cassandra to make informed decisions based on specific requirements and use cases.

Deployment Model: AWS Lambda is a serverless computing service that allows developers to run code without provisioning or managing servers. On the other hand, Cassandra is a distributed database system designed for handling large amounts of data across multiple servers. The key difference lies in the deployment model - Lambda for serverless code execution and Cassandra for distributed data storage.
Computational Focus: AWS Lambda is more focused on executing short-lived functions in response to events, making it ideal for event-driven architectures and microservices. In contrast, Cassandra is a NoSQL database known for its efficient handling of high-velocity, varied data sources, and massive scalability. The difference in computational focus makes Lambda suitable for lightweight, stateless functions and Cassandra for data-intensive applications.
Managed Service: AWS Lambda is a fully managed service provided by Amazon Web Services, which takes care of infrastructure provisioning, scaling, and maintenance. On the other hand, deploying and managing Cassandra clusters require more manual configuration and monitoring efforts by the users. This difference in managed services can impact operational overhead and ease of deployment.
Scaling Behavior: AWS Lambda automatically scales resources based on the incoming request volume, allowing for seamless handling of varying workloads. Cassandra, on the other hand, requires manual configuration and oversight for scaling both horizontally and vertically. The difference lies in the automatic scaling capabilities of Lambda versus the more hands-on approach needed for Cassandra.
Data Structure: AWS Lambda operates on individual functions or tasks, while Cassandra stores data in a schema-free, distributed fashion across a cluster of nodes. This difference in data structure reflects the distinct purposes of the two services - Lambda for processing discrete tasks and Cassandra for storing and querying large volumes of unstructured data efficiently.
Pricing Model: AWS Lambda follows a pay-as-you-go pricing model based on the number of requests and compute time, with no upfront costs or infrastructure fees. In contrast, Cassandra typically involves upfront hardware and deployment costs for setting up clusters, along with ongoing maintenance expenses. The difference in pricing models can affect the cost-effectiveness and budgeting considerations for utilizing either service.

In Summary, understanding the key differences between AWS Lambda and Cassandra can help in selecting the appropriate service based on the specific needs of your applications.