Software Alternatives & Reviews

NumPy VS Qrvey

Compare NumPy VS Qrvey and see what are their differences

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Qrvey logo Qrvey

Embedded Analytics built exclusively for SaaS applications.
Visit Website
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Qrvey Landing page
    Landing page //
    2023-11-21

Qrvey is the only purpose-built solution for embedded analytics

Designed for external use cases where SaaS companies need to provide their customers with powerful and customizable analytics capabilities.

Qrvey is the only full stack solution that offers all the embedded visualization and self-service analytics tools along with a unified data pipeline that offers a data lake optimized for multi-tenant analytics.

Qrvey's embedded visualizations empower engineering teams to build custom experiences, along with full white labeling and CSS customization options to make Qrvey’s javascript widgets blend seamlessly into a SaaS application. ⋅⋅* Qrvey’s data-driven automation workflows enable the creation of complex workflows based on data triggers, such as conditional logic, nested functions, data write-backs with notification integrations to third party systems such as Slack. ⋅⋅* Qrvey supports natural language querying of data using generative AI to easily spot trends and outliers, augmented analysis capabilities. ⋅⋅* Qrvey also supports pixel perfect reporting to generate printable reports from the same analytics data.

Qrvey simplifies data management by providing a single data pipeline solution featuring a data lake solution that is optimized for multi-tenant analytics. This contains native data connectors and APIs to ingest data in any type from any source, including real-time data with live connections. ⋅⋅* Qrvey’s semantic layer can inherit and map security models from your multi-tenant SaaS application, saving software development teams the hassle of duplicating users and roles. ⋅⋅* Qrvey’s robust API allows you to create data delivery services and managed download functions that go beyond basic exporting.

Qrvey is the only complete software solution for embedded analytics that offers SaaS companies the best of both worlds: flexibility and functionality.

NumPy

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website numpy.org
Pricing URL-
Details $
Platforms
-

Qrvey

Categories
  • Business Intelligence
  • Analytics
  • Embedded Analytics
  • Infused Analytics
  • AWS Tools
Website qrvey.com
Pricing URL Official Qrvey Pricing
Details $paid Free Trial
Platforms
Amazon

NumPy features and specs

No features have been listed yet.

Qrvey features and specs

  • Embedded Dashboards: Yes
  • Embedded Dashboard Builders: Yes
  • Embedded Single Charts/Metrics: Yes
  • Embedded Single Chart/Metric Builder: Yes
  • Data Warehouse: Yes
  • ETL: Yes
  • Alerts and Automation: Yes
  • Embedded Pixel-Perfect Reports: Yes
  • Native Multi-Tenant Data Security: Yes
  • Tenant Specific Content Deployment: Yes
  • Prebuilt Data Connectors (Redshift, PostgreSQL, Snowflake, etc): Yes

NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Qrvey videos

Qrvey Embedded Analytics Demo

More videos:

  • Demo - Qrvey Intro Video

Category Popularity

0-100% (relative to NumPy and Qrvey)
Data Science And Machine Learning
Data Dashboard
38 38%
62% 62
Data Science Tools
100 100%
0% 0
Development
0 0%
100% 100

Questions and Answers

As answered by people managing NumPy and Qrvey.

How would you describe your primary audience?

Qrvey's answer:

Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies

Why should a person choose your product over its competitors?

Qrvey's answer:

Customers choose Qrvey for the following reasons:

  • Built for SaaS companies so that's the only focus
  • Fully embeddable that enables customization of the end user experience
  • Flat rate licensing with unlimited users, dashboards, and deployments to developer environments
  • Highly rated customer success and support

What makes your product unique?

Qrvey's answer:

Qrvey's approach to embedded analytics is different. Qrvey combines the best of BI, data warehousing, and data visualization into a single solution built exclusively for SaaS applications.

Qrvey's key features include:

  • 100% Embeddability - Everything is embeddable with JS based components that supports full white labeling so you can create unique analytics experiences within your SaaS application.

  • Data Warehouse included - Visualizations are useless without a scalable data layer built specifically for analytics use cases. Qrvey includes native multi-tenant support so your data is ready for your multi-tenant SaaS application. This includes data syncing and API support that allows for any type of data to be ingested into the Qrvey data layer.

  • Self-Hosted - Deployed to Your AWS Environment. Customers get ultimate control as Qrvey is deployed to their AWS environment inheriting and respecting their security policies. Your data never leaves, but it's ready for analytics now.

User comments

Share your experience with using NumPy and Qrvey. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Qrvey Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Qrvey is an embedded analytics platform used for SaaS data, analytics, and automation technologies. You can deploy it right into your pre-existing AWS account in order to visualize your entire data pipeline. Their start-ups package includes specialized support for pre-launch or early-launch companies, like quick installation and launch, serverless analytics scalability,...
Source: theqalead.com
Top 5 Embedded Analytics Tools for Amazon Redshift (Plus 1 Bonus Option)
Qrvey is an embedded analytics and automation tool designed specifically for SaaS applications. It connects directly to AWS and offers an all-in-one platform that includes data collections, analysis, visualizations, automation, and more.
Source: yurbi.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Qrvey. While we know about 107 links to NumPy, we've tracked only 1 mention of Qrvey. 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.

NumPy mentions (107)

  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 15 days ago
  • JSON in data science projects: tips & tricks
    Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 23 days ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 4 months ago
  • A Comprehensive Guide to NumPy Arrays
    Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 5 months ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 6 months ago
View more

Qrvey mentions (1)

  • Looking for an embedded report builder solution that doesn't require giving a third-party access to the data
    Since you're on AWS already, check out https://qrvey.com. Source: 4 months ago

What are some alternatives?

When comparing NumPy and Qrvey, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.

OpenCV - OpenCV is the world's biggest computer vision library

DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.