YouTube Video
Learn how to supercharge PostgreSQL for time-series data and heavy analytics workloads using the TimescaleDB extension. In this comprehensive course, you will master hypertables, continuous aggregates, and columnar storage by building real-world projects like an AI agent flight recorder and an EV fleet telemetry dashboard.
🏗️ Tiger Data provided a grant to make this course possible.
Get $1,000 credit on Tiger Cloud to follow along: https://tsdb.co/fcc-learn-tsdb
Chapters
- 0:00:00 Introduction & Database Comparison
- 0:01:06 Course Overview
- 0:01:28 Sponsor (Tiger Data & Tigercloud)
- 0:02:27 What is Time Series Data?
- 0:04:19 Projects Overview
- 0:05:24 It's Just PostgreSQL
- 0:06:54 Example Data Setup
- 0:10:20 The 20% of SQL You Need
- 0:19:34 Understanding EXPLAIN & ANALYZE
- 0:24:59 Pages & Row Storage
- 0:26:09 MVCC, Dead Rows & Vacuuming
- 0:29:27 Native Postgres Partitioning vs. TimescaleDB
- 0:32:42 What is a Hypertable?
- 0:33:14 Materialized Views & Summary Tables
- 0:37:05 The Dashboard Problem (Web Analytics Scenario)
- 0:44:14 Creating a Hypertable
- 0:48:43 The Golden Rule: Always Filter by Time
- 0:49:31 How Big Should a Chunk Be?
- 0:54:21 Testing Hypertable Performance
- 0:59:14 Indexing & Chunk Skipping
- 1:03:50 Global Unique Indexes & UUID v7
- 1:13:45 Data Locality & Reordering
- 1:15:42 The Column Store
- 1:18:36 Columnar Compression Techniques
- 1:22:58 Segment By & Order By
- 1:26:15 Converting Chunks to Column Store
- 1:29:03 Compressed Indexes & Bloom Filters
- 1:32:27 Continuous Aggregates
- 1:38:08 Real-Time Aggregates
- 1:40:30 Aggregate Ladders
- 1:44:50 Hyperfunctions & Gap Filling
- 1:50:16 State Aggregates
- 1:52:28 Approximate Aggregates & Percentiles
- 1:55:58 HyperLogLog (Approximate Count Distinct)
- 1:57:26 Other Toolkit Features
- 1:59:30 Data Retention Policies
- 2:04:47 Tiered Storage
- 2:08:42 Docker Setup & Environment Configuration
- 2:16:35 Project 1: AI Agent Flight Recorder
- 2:22:04 Project 1: Schema Design
- 2:28:22 Project 1: Ingestion Script & Batch Copy
- 2:35:45 Project 1: Optimizing the Database
- 2:50:56 Project 1: Querying Raw Data
- 3:00:13 Project 1: API & Dashboard Integration
- 3:15:54 Project 2: EV Fleet Telemetry & TigerCloud
- 3:22:20 Project 2: Schema Design
- 3:25:52 Project 2: The Analytics Join Myth
- 3:27:26 Project 2: Segment By Benchmarking
- 3:42:32 Project 2: Finding Anomalies
- 4:02:13 Project 2: Semantic Search (pgvector)
- 4:08:47 TigerCloud Console Overview
- 4:14:26 12-Step Production Checklist
🏗️ Tiger Data provided a grant to make this course possible.
Get $1,000 credit on Tiger Cloud to follow along: https://tsdb.co/fcc-learn-tsdb
Chapters
- 0:00:00 Introduction & Database Comparison
- 0:01:06 Course Overview
- 0:01:28 Sponsor (Tiger Data & Tigercloud)
- 0:02:27 What is Time Series Data?
- 0:04:19 Projects Overview
- 0:05:24 It's Just PostgreSQL
- 0:06:54 Example Data Setup
- 0:10:20 The 20% of SQL You Need
- 0:19:34 Understanding EXPLAIN & ANALYZE
- 0:24:59 Pages & Row Storage
- 0:26:09 MVCC, Dead Rows & Vacuuming
- 0:29:27 Native Postgres Partitioning vs. TimescaleDB
- 0:32:42 What is a Hypertable?
- 0:33:14 Materialized Views & Summary Tables
- 0:37:05 The Dashboard Problem (Web Analytics Scenario)
- 0:44:14 Creating a Hypertable
- 0:48:43 The Golden Rule: Always Filter by Time
- 0:49:31 How Big Should a Chunk Be?
- 0:54:21 Testing Hypertable Performance
- 0:59:14 Indexing & Chunk Skipping
- 1:03:50 Global Unique Indexes & UUID v7
- 1:13:45 Data Locality & Reordering
- 1:15:42 The Column Store
- 1:18:36 Columnar Compression Techniques
- 1:22:58 Segment By & Order By
- 1:26:15 Converting Chunks to Column Store
- 1:29:03 Compressed Indexes & Bloom Filters
- 1:32:27 Continuous Aggregates
- 1:38:08 Real-Time Aggregates
- 1:40:30 Aggregate Ladders
- 1:44:50 Hyperfunctions & Gap Filling
- 1:50:16 State Aggregates
- 1:52:28 Approximate Aggregates & Percentiles
- 1:55:58 HyperLogLog (Approximate Count Distinct)
- 1:57:26 Other Toolkit Features
- 1:59:30 Data Retention Policies
- 2:04:47 Tiered Storage
- 2:08:42 Docker Setup & Environment Configuration
- 2:16:35 Project 1: AI Agent Flight Recorder
- 2:22:04 Project 1: Schema Design
- 2:28:22 Project 1: Ingestion Script & Batch Copy
- 2:35:45 Project 1: Optimizing the Database
- 2:50:56 Project 1: Querying Raw Data
- 3:00:13 Project 1: API & Dashboard Integration
- 3:15:54 Project 2: EV Fleet Telemetry & TigerCloud
- 3:22:20 Project 2: Schema Design
- 3:25:52 Project 2: The Analytics Join Myth
- 3:27:26 Project 2: Segment By Benchmarking
- 3:42:32 Project 2: Finding Anomalies
- 4:02:13 Project 2: Semantic Search (pgvector)
- 4:08:47 TigerCloud Console Overview
- 4:14:26 12-Step Production Checklist
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