In this tutorial we will use Timescale Cloud to create a live chart of crypto market data.
Timescale is a time-series SQL database providing fast analytics and scalability based on PostgreSQL.

Timescale Database + Pulse Dashboards timescale database cryto dashboard

Creating Real-time Timescale Crypto Dashboards

Creating new Timescale Database

Timescale can either be ran locally or you can use Timescale Cloud. To keep this tutorial simple we opted for cloud. Simply start a small service in your chosen region. The connection details should be provided, similar to shown:

Create Timescale Database Server Timescale Config

Populating the Tables

To populate our tables, we have created a java program that uses org.knowm.xchange to connect to a number of exchanges and forward data to Timescale using the standard Postgres JDBC driver. To run it yourself, download the jar below or see the source in our github repo.

Download pgfeed.jar

To create the tables and run the feed, run it with the parameters:

You should see output similar to below. The periods "." are the feed waiting. The larger letters T/o are it sending Trades and Orders respectively:

Add Timescale PostgreSQL Connection

Download Pulse

Download Pulse. Any platform is fine, then launch pulse.exe or This will open the pulse UI in a web browser.
Click Connections to go to the connections screen.

Pulse Add Connection

Timescale is PostgreSQL (not forked/reimplemented), therefore the standard postgres driver can be used.

To add a connection in Pulse goto Connections->"Add Data Connection" and fill in your details.
You can try clicking test to see if the connection works before adding it.

  • type: Postgres
  • host:
  • port: 31319
  • database: tsdb
  • username: tsdbadmin
  • password: wfs87wik6faoyrs9
Pulse connecting to Timescale database

Note: A very small number of users have received "org.postgresql.util.PSQLException: SSL error: Received fatal alert: handshake_failure" errors when attempting to add a timescale connection. This is due to the SSL certificates available in the java VM they are attempting to use. If this happens, try a different java version or contact us for help

Adding our First Table

  1. On the dashboards listing page, click add
    Add PostgreSQL Dashboard
  2. Click on the newly created dashboard to go into it. Either click on edit or toggle design mode once in the dashboard.
    Edit PostgreSQL Dashboard
  3. On the component bar, click "Table" to add a grid.
    Add Chart to Dashboard
  4. Within the Editor
    • Select the Timescale server
    • Enter the query:

    Timescale Trade Blotter

Adding a Chart

The next SQL chart we want is a time-series. We use UNION to join the quotes + my trades + others trades. So that the bid/ask quotes are shown as lines, while the trades have triangle/circle shapes relative to the size of the trade:

Timescale Time Series Chart

Linking Tables and Charts

Table Click Events allow users to click a row in a table, and have a chart show related data:

  1. When a user clicks a row, the first few column names become populated with the value in that row.
  2. i.e. ((sym))->"BTC/USD" The sym variable maps to the value "BTC/USD".
  3. In the timeseries chart configuration
  4. We can then use ((sym)) in the SQL query and the chart will be updated when the user clicks a row.

Well Done

Well done, we've created our Timescale Crypto Dashboard.

I found Timescale good to work with. Since it's mostly PostgreSQL based I was able to reuse a lot of my existing knowledge.
We added it to our top list of time-series databases.

To me the exciting features of Timescale are:

  • Hypertables - automatically partitions data by time, and optionally by space. Each hypertable is made up of child tables called chunks. Each chunk is assigned a range of time, and only contains data from that range. If the hypertable is also partitioned by space, each chunk is also assigned a subset of the space values.
  • Continuous Aggregates - First, Timescale processes the aggregation calculations when the aggregate is created and then stores the aggregation results to minimize re-calculation when new raw data is added.

Thanks for watching our demo. Please download Pulse to give it a try for yourself.

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