Software Alternatives, Accelerators & Startups

Quantopian VS BigchainDB

Compare Quantopian VS BigchainDB and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Quantopian logo Quantopian

Your algorithmic investing platform

BigchainDB logo BigchainDB

The scalable blockchain database.
  • Quantopian Landing page
    Landing page //
    2023-07-27
  • BigchainDB Landing page
    Landing page //
    2021-12-14

Quantopian features and specs

  • Community Collaboration
    Quantopian provided a platform for users to share and collaborate on trading algorithms, enabling users to learn from each other and improve their strategies.
  • Access to Data
    Quantopian offered access to a wide range of financial data sets, which allowed users to develop and back-test their algorithms using historical data.
  • Comprehensive Development Environment
    It featured an integrated development environment (IDE) with tools for coding, testing, and back-testing trading strategies in Python, which was user-friendly and powerful.
  • Educational Resources
    Quantopian provided various educational resources, including lectures, tutorials, and a supportive community forum, which were beneficial for both beginners and experienced traders.
  • Competition and Incentives
    Quantopian organized contests that incentivized users to develop successful trading algorithms, with the potential to receive a live trading allocation from the company.

Possible disadvantages of Quantopian

  • Shutting Down Services
    Quantopian shut down its retail offering in 2020, which meant that users could no longer use their platform for developing and testing new algorithms.
  • Limited Live Trading Options
    Users found limited options for deploying their strategies into live trading. Quantopian allowed this only for algorithms selected for allocation, which reduced accessibility for many users.
  • Dependence on Platform
    Users who developed algorithms on Quantopian's platform were heavily dependent on it, and when it shut down, they had to transition to other platforms, which could be challenging.
  • Resource Limitations
    There were computational and resource limitations for users, which could restrict the complexity of the algorithms and back-testing users could perform without additional infrastructure.
  • Portfolio Selection Process
    The selection process for having algorithms licenced for live trading allocation was competitive and not transparent to many users, which could lead to frustration.

BigchainDB features and specs

  • Decentralization
    BigchainDB integrates blockchain's decentralization and immutability features, ensuring no single point of failure and enhancing data integrity.
  • Scalability
    Built on top of distributed database technologies, BigchainDB can handle large volumes of transactions and manage significant data sets efficiently.
  • Fast Transaction Processing
    With its efficient consensus mechanism, BigchainDB offers high-speed transaction processing and minimal latency compared to traditional blockchains.
  • Customizable
    BigchainDB provides flexibility for developers to customize and integrate with various applications through its rich API support.
  • Permissioned Network
    BigchainDB can operate within permissioned settings, offering a controlled environment ideal for enterprise-level applications.

Possible disadvantages of BigchainDB

  • Complexity
    The integration of blockchain features with database technology can be complex, posing a steep learning curve for new users.
  • Ecosystem Maturity
    Compared to other blockchain technologies, BigchainDB's ecosystem is less mature, which may result in less community support and fewer third-party integrations.
  • Consensus Mechanism Limitations
    While BigchainDB's consensus mechanism is efficient, it may not be as robust as those of more established blockchains, potentially affecting security in some scenarios.
  • Limited Use Cases
    BigchainDB's unique architecture may not be suitable for all blockchain use cases, specifically those that require fully decentralized environments.
  • Development and Maintenance Costs
    Setting up and maintaining a BigchainDB environment can be resource-intensive, potentially incurring higher costs compared to other solutions.

Quantopian videos

Algorithmic Trading with Python and Quantopian p. 1

More videos:

  • Review - Quantopian, simple strategies

BigchainDB videos

Blockchain Use Case: Medical Records on BigchaindB

More videos:

  • Review - Michael Reh, Tymlez | Real-World Scenarios Using BigchainDB and Tymlez
  • Review - Troy McConaghy - BigchainDB - What's New in BigchainDB 2.0?

Category Popularity

0-100% (relative to Quantopian and BigchainDB)
Finance
100 100%
0% 0
Cloud Infrastructure
0 0%
100% 100
Tool
100 100%
0% 0
Cloud Computing
0 0%
100% 100

User comments

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What are some alternatives?

When comparing Quantopian and BigchainDB, you can also consider the following products

QuantConnect - QuantConnect provides a free algorithm backtesting tool and financial data so engineers can design algorithmic trading strategies. We are democratizing algorithm trading technology to empower investors.

Ethereum - Ethereum is a decentralized platform for applications that run exactly as programmed without any chance of fraud, censorship or third-party interference.

Backtrader - Backtrader is a complete and advanced python framework that is used for backtesting and trading.

Hyperledger - Hyperledger is a multi-project open source collaborative effort hosted by The Linux Foundation, created to advance cross-industry blockchain technologies.

CloudQuant - Crowd based algorithmic trading development and backtesing for stock market trading.

IBM MQ - IBM MQ is messaging middleware that simplifies and accelerates the integration of diverse applications and data across multiple platforms.