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Clearbit VS NumPy

Compare Clearbit VS NumPy and see what are their differences

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Clearbit logo Clearbit

Clearbit provides Business Intelligence APIs

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Clearbit Landing page
    Landing page //
    2023-10-06
  • NumPy Landing page
    Landing page //
    2023-05-13

Clearbit features and specs

  • Extensive Data Coverage
    Clearbit offers comprehensive and up-to-date information on companies and individuals, making it a valuable tool for sales, marketing, and business intelligence.
  • Real-Time API
    The real-time API allows for the instant enrichment of data, enabling users to access detailed information without delays, which is useful for dynamic applications.
  • Seamless Integration
    Clearbit easily integrates with major CRM platforms, email marketing tools, and other software, facilitating its adoption into existing workflows.
  • Enrichment and Prospector Features
    Clearbit offers features like email enrichment and prospecting, helping businesses find and target the right contacts efficiently.
  • Quality of Data
    The data provided by Clearbit tends to be highly accurate, which is crucial for making informed business decisions and campaigns.
  • Enhanced Lead Identification
    The Weekly Visitor Report by Clearbit allows businesses to identify anonymous website visitors by providing detailed company data, which enhances lead generation efforts.
  • Comprehensive Data Insights
    The report provides in-depth information about visitors, such as company size, industry, and location, enabling more targeted marketing strategies.
  • Improved Sales Outreach
    With detailed visitor reports, sales teams can tailor their outreach strategies and prioritize leads based on the potential value and relevance of each visitor.
  • Easy Integration
    Clearbit's platform can be easily integrated with existing CRM systems, ensuring a seamless workflow for tracking and utilizing visitor data.
  • Comprehensive Data
    Clearbit Connect provides detailed information about contacts, including email addresses, company details, and social media profiles, making it easier for businesses to find and verify leads.
  • Ease of Use
    The extension integrates seamlessly with Gmail and G Suite, making it straightforward for users to gather information without leaving their email interface.
  • Time-Saving
    Clearbit Connect automates the process of finding contact information, reducing the time spent on manual search and allowing users to focus on outreach efforts.
  • Free Tier Availability
    A free version is available which allows users to access basic features without any initial cost, making it accessible for small businesses and startups.
  • Reliability
    Clearbit is known for providing accurate data, reducing the chances of bounced emails and improving overall outreach effectiveness.

Possible disadvantages of Clearbit

  • Cost
    Clearbit can be expensive, particularly for small businesses or startups with limited budgets. The pricing model may not be feasible for all organizations.
  • Data Privacy Concerns
    As Clearbit collects and provides detailed personal and corporate data, there may be concerns about privacy and compliance with data protection regulations.
  • Data Variability
    While the data is generally accurate, there can be occasional inconsistencies or outdated information which could affect decision-making.
  • Technical Integration Complexities
    Although Clearbit offers many integrations, setting them up and maintaining them can sometimes be complex and require technical expertise.
  • Dependency on Internet
    Using Clearbit's real-time API requires a stable internet connection, which could be a limitation in areas with poor connectivity.
  • Cost Considerations
    Clearbit's comprehensive data services can be expensive, especially for startups or small businesses with limited budgets.
  • Accuracy Limitations
    While Clearbit provides extensive data, the accuracy and timeliness of the information may sometimes be limited, potentially affecting decision-making.
  • Complexity in Setup
    For businesses without a dedicated IT team, the initial setup and integration of Clearbit’s services can be complex and require technical expertise.
  • Limited Free Usage
    The free tier has limitations on the number of searches and data available, which may require users to upgrade to a paid plan for higher volume needs.
  • Privacy Concerns
    Some users may have concerns about the privacy of their data, as Clearbit collects and processes a significant amount of personal and company information.
  • Data Freshness
    While generally reliable, occasionally the provided data may not be up-to-date, leading to outdated contact information.
  • Integration Issues
    There may be occasional issues or bugs with the Gmail integration, causing some users to experience interruptions in their workflow.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Clearbit videos

The Weekly Visitor Report by Clearbit

More videos:

  • Review - Clearbit - Reev & OTB | Outbound Reviews #6
  • Review - Clearbit Lead Enrichment Automations and Integrations (2019)
  • Review - E996 Clearbit CEO Alex MacCaw is creating god-mode for marketers, prioritizing profitability

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

Category Popularity

0-100% (relative to Clearbit and NumPy)
Lead Generation
100 100%
0% 0
Data Science And Machine Learning
Sales Tools
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

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

Clearbit Reviews

Top 13 ZoomInfo Alternatives
Clearbit is all about quality data. This solution is designed for smarter scoring, better routing, and more revenue. Clearbit automatically updates sales records with the accurate company and contact data.
Source: taskdrive.com

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

Social recommendations and mentions

Based on our record, NumPy should be more popular than Clearbit. It has been mentiond 119 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.

Clearbit mentions (12)

  • Show HN: Every problem and solution in Beyond Cracking the Coding Interview
    We use Clearbit for enrichment: https://clearbit.com/. - Source: Hacker News / 20 days ago
  • Ask HN: What happens when I click "Request for quote" on your SaaS?
    Pretty sure that's exactly what Clearbit does. Although now their site has some AI hype on it and I can't tell if that's just the obligatory AI marketing, or if they actually changed their product. https://clearbit.com/. - Source: Hacker News / 12 months ago
  • How Profile Enrichment can boost your product
    For profile enrichment with Authgear, you create a Hook that could call an external API such as FullContact and Clearbit to grab some data and then put any extra information into the User Profile that every user gets when they sign up through Authgear. You could also integrate that data with the profile custom attributes of existing users who are logging in but are missing that information. - Source: dev.to / almost 2 years ago
  • Getting Your Developers to See Value With a Great Developer Experience
    Leveraging an extension like Clearbit will help you surface the relevant demographic information, such as role, industry, and company size. This will then allow you to zero in on who is likely to be your next best customer. - Source: dev.to / almost 3 years ago
  • Legality and ethics question about a feature I saw on a website
    I inspected the site a bit and it looks like they're using https://clearbit.com/ to get the company data. Personally I don't feel there is any ethical issue however everyone has their own opinions. It definitely feels a bit creepy. Source: almost 3 years ago
View more

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 5 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

What are some alternatives?

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

Lusha - Search less. Sell more.

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

DiscoverOrg - DiscoverOrg is an IT sales intelligence platform providing technology marketers access to data, IT org charts, and real time projects.

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

ZoomInfo - ZoomInfo is a B2B database providing detailed business information on people and companies.

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