Versus
    32-bit vs 64-bit
    Annotations vs Decorators
    BigQuery vs Bigtable
    Block Storage vs File Storage vs Object Storage
    C vs C++
    Canvas vs SVG
    Constructor vs Init() vs Factory
    Containers vs Virtual Machines (VMs)
    DOM vs Virtual DOM vs Shadow DOM
    DQL vs DDL vs DCL vs DML
    Dagger vs Guice
    Data Mining vs Machine Learning vs Artificial Intelligence vs Data Science
    Flux vs Redux
    GCP API Gateway vs Cloud Endpoint
    GCP Cloud Run vs Cloud Functions vs App Engine
    GCP DataFlow vs Dataproc
    Google Analytics 4 vs Universal Analytics
    Google Internal vs Open Source
    HEIC vs HEIF vs HEVC vs JPEG
    Java vs C++
    Jetty vs Netty
    Kotlin vs Java
    LLVM vs JVM
    Linux vs BSD
    Microcontroller vs Microprocessor vs Computer
    Node.js vs Erlang
    POSIX vs SUS vs LSB
    Pass-by-value vs Pass-by-reference
    Proto2 vs Proto3
    PubSub vs Message Queue
    REST vs SOAP
    React vs Flutter vs Angular
    Rust vs C++
    SLI vs SLO vs SLA
    SRAM vs DRAM
    SSD vs HDD
    Software Engineer vs Site Reliability Engineer
    Spanner vs Bigtable
    Stack based VM vs Register based VM
    Stateless vs Stateful
    Static Site Generation vs Server-side Rendering vs Client-side Rendering
    Strong Consistency vs Eventual Consistency
    Subroutines vs Coroutines vs Generators
    Symlinks vs Hard Links
    TCP vs UDP
    Tensorflow vs PyTorch
    Terminal vs Shell
    Vi vs Vim vs gVim vs Neovim
    WAL vs rollback journal
    gtag vs Tag Manager
    stubs vs mocks vs fakes

Data Mining vs Machine Learning vs Artificial Intelligence vs Data Science

Updated: 2022-02-12

There are no clear boundaries among these terms

Machine learning

More like another name of "statistics", but in computer science.

Data Mining

Data Mining == Knowledge Discovery in Databases(KDD)

This may no longer be the accurate definition of data mining, since data can be stored in a data lake(like on HDFS of a Hadoop cluster) but not necessarily in a database.

The scope, summarized in wikipedia:

it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.

Artificial Intelligence

A much broader term, machine learning is a big part of it.