Software Alternatives, Accelerators & Startups

CloudQuant VS Embeddable

Compare CloudQuant VS Embeddable 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.

CloudQuant logo CloudQuant

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

Embeddable logo Embeddable

The toolkit for building fast, interactive, fully-custom analytics experiences into your app.
  • CloudQuant Landing page
    Landing page //
    2021-08-01
  • Embeddable Headless Embedded Analytics
    Headless Embedded Analytics //
    2025-03-18

Build Remarkable Analytics Experiences. No more 'Build vs. Buy'. Embeddable is the embedded analytics tool where you own the front-end code and we handle everything else. Now you can build fully-bespoke, fast-loading charts and dashboards in your app without the engineering costs. Delight your customers, reduce engineering overheads, and deliver your dream experience, fast. Compatible with all major databases. Cloud & Self-hosted. Multi-tenancy. Open source component library + more

CloudQuant features and specs

  • Data Variety
    CloudQuant provides access to a wide range of alternative datasets, enabling users to explore diverse data sources for more informed trading strategies.
  • Backtesting Features
    The platform offers robust backtesting tools, which allow users to test their trading algorithms under historical market conditions to evaluate their performance.
  • Collaborative Environment
    CloudQuant fosters a collaborative environment where users can share strategies and insights with a community of other developers and traders.
  • Python-Based
    The platform supports Python programming, which is popular among developers for its simplicity and extensive library support, making it accessible for quantitative research.

Possible disadvantages of CloudQuant

  • Learning Curve
    New users may face a steep learning curve, particularly if they are unfamiliar with quantitative analysis or programming, which can be a barrier to entry.
  • Cost
    Accessing advanced features or specific datasets on CloudQuant may incur significant costs, which could be prohibitive for individual traders or small firms.
  • Dependence on Internet
    As with any cloud-based platform, using CloudQuant requires a reliable internet connection, which can be a limitation in areas with unstable connectivity.
  • Complexity for Beginners
    The complexity of the platform might overwhelm beginners who might find it challenging to navigate the advanced features without prior experience or guidance.

Embeddable features and specs

  • Cloud-Hosted Option
  • Self-Hosted Option
  • Frontend SDK
  • No-code Dashboard Builder
  • Performant Embedding
  • Row-Level Security
  • Configurable Cache
  • Compatible with Major Databases
  • Compatible with Charting Libraries
  • Template Charting Components Provided
    Included
  • Dedicated Account Management
  • Version Control
  • Audit Logs
  • Documentation

CloudQuant videos

Advanced 1 - CloudQuant presentation for theย University of Chicago Financial Program

More videos:

  • Review - SMB Quant (002): โ€œDemocratization of Tradingโ€ with Paul Tunney from CloudQuant

Embeddable videos

No Embeddable videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to CloudQuant and Embeddable)
Finance
100 100%
0% 0
Business Intelligence
0 0%
100% 100
Tool
100 100%
0% 0
Data Dashboard
0 0%
100% 100

Questions & Answers

As answered by people managing CloudQuant and Embeddable.

How would you describe the primary audience of your product?

Embeddable's answer:

Software companies who care about the UX and loading speed of their customer-facing analytics.

What makes your product unique?

Embeddable's answer:

Get the best of 'Build vs. Buy' in one stack-agnostic solution. Embeddable gives you full control over the frontend of your analytics experience, and handles the backend for you. No longer do you have to choose between a limited out-of-the-box solution, or building everything from scratch.

What's the story behind your product?

Embeddable's answer:

Embeddable is from the team behind Trevor.io -- a popular internal BI tool which also allows you to embed dashboards into your app. We realised embedding dashboards from a BI tool into your app wasn't the 'dream solution', and building analytics from scratch was super expensive... so we built Embeddable from the ground up to enable teams to deliver fully-bespoke, highly-performant analytics in their apps for their customers in 10% of the time.

Who are some of the biggest customers of your product?

Embeddable's answer:

  • Scalapay
  • Adthena
  • Irwin
  • EtonX
  • Resident Advisor
  • Facilities Solutions Group (FSG)
  • Multibrain
  • Raydiant
  • ThinkCERCA
  • Tixly
  • Softools
  • Faheem App
  • Just Move In
  • Any Creek

Why should a person choose your product over its competitors?

Embeddable's answer:

If you want full control over the UX of your customer-facing analytics experience, but don't want to invest months of developer time on building and maintaining a fully-custom build -- OR -- if you're using an embedded analytics too already that loads slowly and doesn't look and feel like the rest of your platform.

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare CloudQuant and Embeddable

CloudQuant Reviews

We have no reviews of CloudQuant yet.
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Embeddable Reviews

6 Best Looker alternatives
After a successful, oversubscribed Private Beta, Embeddable is now publicly available. More information on how to work with Embeddable can be found on their homepage at embeddable.com. Get in touch with the Embeddable team for pricing.
Source: trevor.io
Power BI Embedded vs Looker Embedded: Everything you need to know
The main differences between Power BI Embedded and Embeddable are performance, price, and customizability. Embeddable gives you full control over your charting components and data models. Itโ€™s also built from the ground up to enable companies to deliver fully bespoke, highly-performant analytics experiences to their customers, without requiring an expensive in-house build....
Source: embeddable.com
Embedded analytics in B2B SaaS: A comparison
Iโ€™m happy to say that weโ€™ve enrolled in the beta program of Embeddable. After learning all the above it seems like this is the option weโ€™d want to invest in. Weโ€™ll keep you posted on how this pans out, but weโ€™re excited about what Embeddable is building and is going to offer.
Source: medium.com

Social recommendations and mentions

Based on our record, Embeddable seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

CloudQuant mentions (0)

We have not tracked any mentions of CloudQuant yet. Tracking of CloudQuant recommendations started around Mar 2021.

Embeddable mentions (2)

  • AI in BI tools: why we're not there yet
    Then comes data modeling. BI tools such as Embeddable need to know how different tables and fields relate to each other. Someone has to define what terms like โ€œtop customerโ€ or โ€œQ3 revenueโ€ actually mean. Without this, the AI won't know where to look or how to answer even basic questions. - Source: dev.to / about 1 year ago
  • Apache Superset
    Itโ€™s still pretty new but build by an experienced team. Itโ€™s commercial software though. https://embeddable.com/. - Source: Hacker News / over 2 years ago

What are some alternatives?

When comparing CloudQuant and Embeddable, you can also consider the following products

Quantopian - Your algorithmic investing platform

Luzmo - From data to decisions, damn fast. Embed beautiful, easy-to-use dashboards in your SaaS product in days, not months.

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.

Metabase - Metabase is the easy, open source way for everyone in your company to ask questions and learn from...

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

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.