Talk Python To Me

#420: Database Consistency & Isolation for Python Devs

35 snips
Jun 26, 2023
Ask episode
Chapters
Transcript
Episode notes
1
Introduction
00:00 • 2min
2
MongoDB Labs: A Research Organization
01:48 • 2min
3
The Differences Between PyMongo and Motor
03:34 • 4min
4
The Differences Between C++ and Python
07:10 • 2min
5
The Future of Python Performance
08:50 • 2min
6
Predictive Scaling for Atlas
10:31 • 2min
7
Atlas Serverless: Predictive Scaling in Atlas
12:48 • 3min
8
The Importance of Consistency and Isolation in Python
15:31 • 2min
9
The Different Types of Databases
17:54 • 2min
10
The Impedance Mismatch in No Sequel Databases
19:40 • 2min
11
The Future of Data Mining
21:36 • 2min
12
The Importance of Consistency and Isolation in Relational Data
23:30 • 2min
13
Python Locks for Key Value Stores
25:21 • 2min
14
InfluxDB: A Database for Real-Time Analytics
27:06 • 4min
15
MongoDB: The Default Way to Do Transactions
31:15 • 3min
16
The Relationship Between Consistency and Isolation Levels
34:30 • 2min
17
Why Read Committed Anomalies Exist
36:24 • 2min
18
The Relationship Between Data Consistency and Scalability
38:38 • 2min
19
The Importance of Consistency in a Distributed Database
40:19 • 3min
20
The Challenges of a Replica Set
43:28 • 2min
21
The Importance of Read Preferences in MongoDB
45:47 • 2min
22
The Importance of Causal Consistency in MongoDB
47:21 • 2min
23
How to Keep the Counter Store Consistent When You Need to Replicate It Across Regions
48:55 • 2min
24
The Importance of Linearizability in MongoDB
50:43 • 2min
25
The Importance of Databases in Computing
52:40 • 3min