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Production Data Systems Handbook
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01
The Real Shape of a Production Data System
12:42
02
Workload Fingerprints: Requirements Before Products
12:42
03
Invariants: The Facts That Must Survive
15:46
04
The Cost of a Database Choice
20:07
05
Data Models and Query Shapes
21:58
06
Storage Engines: B-Trees, LSM Trees, Column Stores, and Object Storage
19:47
07
Indexes and Access Paths
15:54
08
Transactions, Isolation, and Concurrency Anomalies
18:59
09
Replication, Consensus, Sharding, and Multi-Region Reality
17:35
10
Time, Ordering, Idempotency, and Exactly-Once Myths
14:27
11
Caches, Derived Data, and Materialized Views
17:23
12
Schemas, Contracts, Metadata, and Meaning
17:24
13
The Decision Room: A Repeatable Database Selection Process
17:35
14
Relational Systems: The Default You Should Understand Before Replacing
13:27
15
Key-Value, Document, and Wide-Column Stores
16:00
16
Search Systems: Text, Relevance, and Retrieval Are Not Just Filters
15:54
17
Event Logs, Queues, and Streams
17:30
18
Analytical Stores: Warehouses, Lakes, Lakehouses, and OLAP Serving
13:50
19
Time-Series Systems and Observability Stores
14:21
20
Graph Systems
12:38
21
Vector Stores, Feature Stores, and AI-Adjacent Data Systems
16:16
22
Polyglot Persistence Without Distributed Regret
14:41
23
Modeling Writes: Commands, Transactions, Events, and Side Effects
14:12
24
Modeling Reads: Query APIs, Read Models, and Freshness
15:33
25
Data APIs and Service Boundaries
16:03
26
Multi-Tenancy, Identity, Authorization, and Data Isolation
16:02
27
Ingestion, CDC, Outbox, and Data Movement
15:11
28
Batch, Streaming, Reprocessing, and Reconciliation
14:05
29
Capacity Planning, Load Testing, and Cost Modeling
15:04
30
Schema and Index Migrations Without Downtime
14:08
31
Data Migrations, Backfills, and Cutovers
16:04
32
Evolving Data Models and APIs Under Consumer Pressure
19:04
33
Retiring, Archiving, and Deleting Data Systems
23:21
34
Observability for Data Systems
16:47
35
Query Performance and Execution Plans
22:17
36
Locks, Contention, Hot Keys, and Tail Latency
20:20
37
Data Correctness Bugs, Drift, and Reconciliation
24:23
38
Distributed Failure Debugging
17:16
39
Testing Data Systems: Properties, Faults, and Production Confidence
12:03
40
SLOs, SLIs, and Error Budgets for Data Systems
17:16
41
Backup, Restore, Disaster Recovery, and Business Continuity
21:31
42
On-Call, Runbooks, Incidents, and Postmortems
17:37
43
Security, Privacy, Compliance, and Abuse Resistance
21:39
44
Data Quality, Governance, Lineage, and Ownership
16:52
45
Building a Data Platform: Paved Roads, Guardrails, and Escape Hatches
18:44
46
FinOps for Data Systems: Cost as a Design Constraint
20:50
47
Ethics, User Trust, and Organizational Decision Quality
12:39
48
Case Study: E-Commerce Catalog, Inventory, Cart, and Search
15:24
49
Case Study: Payments, Ledger, and Financial Correctness
16:53
50
Case Study: Event-Driven Notifications and Workflow
14:15
51
Case Study: Metrics, Logs, Traces, and Time-Series Explosion
13:52
52
Case Study: Analytics Warehouse and Revenue Reporting
18:31
53
Case Study: Multi-Region SaaS and Tenant Isolation
15:35
54
Case Study: AI/RAG Knowledge Base with Vector Search
21:41
