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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. AWS Lambda vs TiDB

AWS Lambda vs TiDB

OverviewDecisionsComparisonAlternatives

Overview

AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432
TiDB
TiDB
Stacks76
Followers177
Votes28
GitHub Stars39.3K
Forks6.0K

AWS Lambda vs TiDB: What are the differences?

Introduction

Key differences between AWS Lambda and TiDB:

  1. Deployment and Scalability: AWS Lambda is a serverless computing service where you upload your code and Lambda takes care of everything required to run and scale the code with high availability. On the other hand, TiDB is a distributed SQL database that can be deployed on-premises or on the cloud and offers horizontal scalability by adding more nodes to the cluster.

  2. Programming Language Support: AWS Lambda supports multiple programming languages such as Node.js, Python, Java, and C#, allowing developers to choose the language that best suits their needs. In contrast, TiDB primarily supports SQL queries and transactions, making it more tailored for database operations rather than general-purpose computing.

  3. Functionality: AWS Lambda is designed for event-driven, serverless computing where functions are triggered by events, making it ideal for microservices architecture and quick development cycles. On the contrary, TiDB is a distributed database focused on providing horizontal scalability, high availability, and strong consistency for mission-critical applications that require complex data processing and multi-region deployment.

  4. Pricing Model: AWS Lambda follows a pay-per-use pricing model where you are charged for the number of requests and the duration of execution, allowing cost-effective operation for sporadic workloads. TiDB, being a database, typically follows a subscription-based or per-instance pricing model, ensuring predictable costs for ongoing operations but may not be as flexible for fluctuating workloads.

  5. Managed Service vs Self-Hosted: AWS Lambda is a managed service where Amazon takes care of the infrastructure, security, and maintenance, allowing developers to focus on writing code without worrying about operational tasks. TiDB, on the other hand, requires self-hosting or using a managed service like TiDB Cloud, requiring more operational expertise but providing more control over the deployment environment.

  6. Consistency and ACID Compliance: AWS Lambda is eventually consistent and does not offer built-in support for ensuring the ACID properties of transactions. TiDB, being a distributed database, ensures strong consistency and provides features like distributed transactions and multi-version concurrency control for maintaining data integrity and reliability in complex scenarios.

In Summary, the key differences between AWS Lambda and TiDB lie in their deployment models, programming language support, functionality focus, pricing models, management approach, and consistency guarantees.

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Advice on AWS Lambda, TiDB

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS 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

Detailed Comparison

AWS Lambda
AWS Lambda
TiDB
TiDB

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.

Inspired by the design of Google F1, TiDB supports the best features of both traditional RDBMS and NoSQL.

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
Horizontal scalability;Asynchronous schema changes;Consistent distributed transactions;Compatible with MySQL protocol;Written in Go;NewSQL over TiKV;Multiple storage engine support
Statistics
GitHub Stars
-
GitHub Stars
39.3K
GitHub Forks
-
GitHub Forks
6.0K
Stacks
26.0K
Stacks
76
Followers
18.8K
Followers
177
Votes
432
Votes
28
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
  • 9
    Open source
  • 7
    Horizontal scalability
  • 5
    Strong ACID
  • 3
    HTAP
  • 2
    Mysql Compatibility

What are some alternatives to AWS Lambda, TiDB?

MongoDB

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

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

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

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

SQLite

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.

Cassandra

Cassandra

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.

Memcached

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

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

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

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.

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