How to store tick data efficiently for analysis and backtest in my local system ?

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How to store tick data efficiently for analysis and backtest in my local system ?

Harkishan Singh Baniya

posted

Recently, I subscribed to a data vendor for getting a long history (last 10 years) of Equity tick data. They provide it via API calls. So, I want an efficient way to store it in my local hard disk for analysis and backtest. Generally, I needed a suggestion on what to use like shall I use a flat-file or a Relational DB or something like MongoDB or NoSQL DB or Apache Parquet etc. The only requirements are that - 1) Faster Loading and Query 2) Size of the file (lesser is better).

Note : Please make sure your solution is Python programmer-friendly :)

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.