Skip to content

A powerful time-series database built on PostgreSQL, optimized for handling time-series data at scale. This repository includes detailed instructions for setting up, configuring, and using TimeScaleDB to store and manage large volumes of time-based data efficiently, with step-by-step guides on best practices and performance tuning.

Notifications You must be signed in to change notification settings

mukeshbadgujar/TimeScaleDB

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

TimescaleDB Usecase Document

Online and Offline Installation with Docker

1. Online Installation

If You want to go with Online https://www.timescale.com/

follow the below steps

  1. Create an account in https://www.timescale.com/ img.png

  2. Choose Service img_1.png

  3. Choose the plan img_2.png

  4. Server Type img_3.png

  5. eave it blank img_4.png

  6. finally it will look like below img_5.png

  7. download files img_6.png

  8. Start Working with TimescaleDB

2. Offline Installation with Docker

  1. Install TimeScaleDB with Docker
docker run -d --name timescaledb \
  -p 5432:5432 \
  -e POSTGRES_PASSWORD=yourpassword \
  timescale/timescaledb:latest-pg14
  1. Create a Database and connect to it
psql -h localhost -U postgres

Note: make sure you have postgresql-client installed in your system

sudo apt update
sudo apt install postgresql-client-common postgresql-client
  1. Create a new database:
CREATE DATABASE timeseries_db;
  1. Enable the TimeScaleDB extension:
\c timeseries_db
CREATE EXTENSION IF NOT EXISTS timescaledb;
  1. Install Python Dependencies
pip install psycopg2 sqlalchemy timescale-client

# for ubuntu
sudo apt-get install -y python3-psycopg2
pip install psycopg2-binary
  1. create db_config.py file
  2. create setup_timescale.py file
  3. run setup_timescale.py file
python setup_timescale.py
INFO:root:Hypertable created.
INFO:root:Sample data inserted.
INFO:root:Aggregated Data:
INFO:root:Sensor ID: 2, Avg Temp: 23.100000000000005, Max Humidity: 59.8
INFO:root:Sensor ID: 1, Avg Temp: 22.199999999999996, Max Humidity: 61.2

now you can start working with timescaledb

About

A powerful time-series database built on PostgreSQL, optimized for handling time-series data at scale. This repository includes detailed instructions for setting up, configuring, and using TimeScaleDB to store and manage large volumes of time-based data efficiently, with step-by-step guides on best practices and performance tuning.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages