[TiDB Quick Start] Study Notes

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Note:
This topic has been translated from a Chinese forum by GPT and might contain errors.

Original topic: 【TiDB 快速起步】学习笔记

| username: TiDBer_诸岳

Course address: https://learn.pingcap.com/learner/course/6

Mind Map Summary

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01 History and Trends of Database and Big Data Development

  1. Drivers of data technology development
    1. Business growth leading to increased data volume
    2. Scenario innovation driving the need for “data interaction efficiency and data model diversity”
    3. Development of hardware and cloud computing
  2. Segmentation of data technology and integration of data services
  3. The essence of the data technology stack or data products: Addressing different business scenarios, making various trade-offs in data technology domain architecture based on these relatively fixed foundational data technology elements

02 Development of Distributed Relational Databases

  1. If the growth rate of the computational load your system needs to handle exceeds Moore’s Law, a centralized system will not be able to handle the required computational load
  2. Distributed is synonymous with massive data and computation
  3. Key challenges of distributed systems: divide and conquer, global consistency, fault amplification, partition tolerance
  4. Although expressing the concept of consistency, the scenarios described by CAP (replica consistency) and ACID (transaction consistency) are different

03 Evolution of TiDB Product and Open Source Community

  1. Raft is an important foundation in distributed systems
  2. The open-source model is one of the best paths to success for foundational software
  3. TiDB is already a top-tier international open-source project

04 What Kind of Database Do We Really Need

  1. Six design goals of distributed relational databases
    1. Horizontal scalability
    2. Strong consistency and high availability
    3. Standard SQL and transaction model
    4. Cloud-native
    5. HTAP
    6. Ecosystem compatibility
  2. The development of hardware, especially networks, has driven the architecture of compute-storage separation
  3. TiDB has a highly layered architecture

05 How to Build a Distributed Storage System

Using the highly layered TiKV transaction + storage engine as an example

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06 How to Build a Distributed SQL Engine

Using the TiDB-Server SQL engine as an example

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07 HTAP Database Based on Distributed Architecture

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08 Key Technological Innovations of TiDB

  1. Layered distributed architecture
  2. Automatic sharding and scheduling
  3. Cross-IDC single-table multi-point writing
  4. Decentralized distributed transactions
  5. Local Read and Geo-partition
  6. Integration of TP and AP

09 Typical Application Scenarios and User Cases of TiDB

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10 First Experience with TiDB

  1. Using TiUP, set up a local test cluster in a few minutes, and automatically install TiDB Dashboard and Grafana, supporting MacOS

https://docs.pingcap.com/zh/tidb/stable/quick-start-with-tidb#%E9%83%A8%E7%BD%B2%E6%9C%AC%E5%9C%B0%E6%B5%8B%E8%AF%95%E9%9B%86%E7%BE%A4

  1. Self-service activation of TiDB Cloud, free trial for one year https://tidbcloud.com/
  2. Online experience of TiDB’s SQL execution: https://tour.pingcap.com/
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| username: redgame | Original post link

:wave: :+1:

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| username: Fly-bird | Original post link

Learned a lot, you’re a good person.