Orus DSL: Enter a new era of crypto analytics

Orus DSL: Enter a new era of crypto analytics

What is a DSL?

A Domain Specific Language is a programming language with a higher level of abstraction optimised for a specific class of problems. A DSL uses the concepts and rules from the field or domain.

The definition sounds much more complicated than it actually is.

A DSL in essence is a language that is designed for a specific use case, compared to general purpose languages.

Orus DSL was designed with the intentions to make your data journey experiences much more streamlined and enjoyable. It allows for great flexibility and speed. The main purpose of the DSL is to offer an easy way to get data on your charts, by defining exactly what you want and how you want it.


Why we choose to build a DSL?

Analysing data in crypto is difficult and often lacks flexibility. The main issues are the way the data is organised which leads to difficulties when you want to organise and structure your charts.

On the other hand, Google’s BigQuery or Dune offer that flexibility, but they are expensive and require extensive SQL knowledge, which is why it’s not an optimal choice for everyone.

There is no way in the current space for people outside of tech to choose which metrics to render on charts outside of what is already provided by your platforms of choice. Beside that, analysts are often required to use data from different places to satisfy all of their needs and companies are required to have dedicated data engineering teams which tends to be very expensive.


Orus DSL provides the best of both worlds:

  1. Ease of use
  2. Modularity and customisability


Orus DSL in practice

In this guide, the base features of the DSL will be presented. There is a lot more to it, and will be explained in a separate post to make your journey with Orus easier.

Orus DSL contains 5 base parts:

  1. Delimiters → what is the type of data
  2. Tickers → what are the samples of those types
  3. Functions → what are the metrics
  4. Graph type → how to render the data
  5. Timeframe

Delimiters and tickers go side by side. They work like filters that you apply when requesting data.

[ETH, POLYGON]C -> Filter data for Ethereum and Polygon chains
[USDC, USDT, DAI]A -> Filter data for USDC, USDT, DAI assets        

Putting it all together

Orus is designed to help you explore questions.

What is the transaction volume (TXV) of USDC and USDT assets on Ethereum chain in the past 180 days?

[ETH]C [USDC, USDT]A TXV G 180D        

What is the TVL of all L1 chains in the past 3 months?

[L1]SEC TVL G 3M        

What is the number of new pools (NPC) on all Uniswap applications on Ethereum chain in the past year?

[ETH]C [UNI*]APP NPC G 1Y        


Looking at all these literals might frighten you, but they are just keywords. Orus will suggest the options as you type so you don’t need to memorise everything from the beginning. For a comprehensive summary of available data, check out our docs.

Can you imagine the flexibility you have for exploratory data analysis?Solve problems faster and unlock advanced analytics using our DSL.Schedule a demo call with us!

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