Best Algorithmic Trading Software for Amazon Web Services (AWS)

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Compare the Top Algorithmic Trading Software that integrates with Amazon Web Services (AWS) as of November 2025

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This a list of Algorithmic Trading software that integrates with Amazon Web Services (AWS). Use the filters on the left to add additional filters for products that have integrations with Amazon Web Services (AWS). View the products that work with Amazon Web Services (AWS) in the table below.

What is Algorithmic Trading Software for Amazon Web Services (AWS)?

Algorithmic trading software enhances and automates trading capabilities for trading financial instruments such as equities, securities, digital assets, currency, and more. Algorithmic trading software, also known as algo trading software or automated trading software, enables the automatic execution of trades depending on occurrences of specified criteria, indicators, and movements by connecting with a broker or exchange. Compare and read user reviews of the best Algorithmic Trading software for Amazon Web Services (AWS) currently available using the table below. This list is updated regularly.

  • 1
    Tradetron

    Tradetron

    Tradetron Inc.

    Tradetron.tech is a algo strategy marketplace ... allows one to build algo strategies without coding (patent pending technology) and other investors to subscribe them and take trades in their own linked brokerage accounts automatically. Its linked with 8 exchanges covering stocks, options, commodities, currencies, crypto currencies and linked with 35 brokers in US and Indian markets. Some 10000 algos are deployed on our system which take 1.5 million trades every month in paper trading and live accounts and we send notifications to users via whatsapp, sms, email and phone call.
    10 Ratings
    Starting Price: $50 per month
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  • 2
    QuantRocket

    QuantRocket

    QuantRocket

    QuantRocket is a Python-based platform for researching, backtesting, and trading quantitative strategies. It provides a JupyterLab environment, offers a suite of data integrations, and supports multiple backtesters: Zipline, the open-source backtester that originally powered Quantopian; Alphalens, an alpha factor analysis library; Moonshot, a vectorized backtester based on pandas; and MoonshotML, a walk-forward machine learning backtester. Built on Docker, QuantRocket can be deployed locally or to the cloud and has an open architecture that is flexible and extensible.
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