Software Alternatives, Accelerators & Startups

Apollo.io VS Deepnote

Compare Apollo.io VS Deepnote 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.

Apollo.io logo Apollo.io

Apolloโ€™s predictive prospecting, sales engagement, and actionable analytics help the teams to reach its full revenue potential.

Deepnote logo Deepnote

A collaboration platform for data scientists
  • Apollo.io Landing page
    Landing page //
    2023-05-08
  • Deepnote Landing page
    Landing page //
    2023-10-09

Apollo.io features and specs

  • Comprehensive Database
    Apollo.io offers a vast and up-to-date contact database, which is ideal for lead generation and sales prospecting.
  • Advanced Search Filters
    The platform provides powerful filtering options that allow users to narrow down potential leads by various criteria, making it easier to target specific audiences.
  • Integration Capabilities
    Apollo.io integrates seamlessly with popular CRM tools like Salesforce and HubSpot, streamlining the workflow for sales teams.
  • Email Tracking
    The email tracking feature helps sales teams monitor engagement and follow up effectively, thereby increasing the chances of closing deals.
  • Customization and Automation
    Users can customize outreach templates and automate follow-up sequences, improving efficiency and ensuring consistent communication.

Possible disadvantages of Apollo.io

  • Pricing
    The platform can be expensive, especially for small businesses or startups with limited budgets.
  • Data Accuracy
    Some users report that contact information can occasionally be outdated or inaccurate, leading to ineffective outreach.
  • Learning Curve
    The platform's extensive features may require a significant amount of time to learn and utilize effectively, posing challenges for new users.
  • Support Limitations
    Customer support may not be as responsive or comprehensive as some users would like, potentially leading to delays in issue resolution.
  • Overdependence on Technology
    Relying too much on the platform's automation features can sometimes lead to reduced personalization in outreach efforts, which can affect engagement.

Deepnote features and specs

  • Collaborative Features
    Deepnote allows for real-time collaboration, similar to Google Docs, where multiple users can work on the same notebook simultaneously without conflicts.
  • Integration with Popular Tools
    Deepnote integrates seamlessly with popular data sources and tools such as Google Drive, GitHub, and SQL databases, enhancing its versatility for data science projects.
  • User-Friendly Interface
    The interface is clean and easy to navigate, making it accessible for both beginners and experienced data scientists.
  • Cloud-Based
    Being a cloud-based solution, Deepnote eliminates the need for local setup and maintenance, allowing users to access their projects from anywhere with internet access.
  • Data Security
    Deepnote provides robust security features, ensuring that your data and notebooks are protected against unauthorized access.
  • Integrated Version Control
    Version control within Deepnote allows users to track changes, revert to previous versions, and collaborate more effectively on shared projects.

Possible disadvantages of Deepnote

  • Limited Offline Access
    As a cloud-based platform, Deepnote requires an internet connection for most of its functionality, which can be a limitation for users needing offline access.
  • Performance Constraints
    Heavy computational tasks might be limited by the performance capabilities of the cloud resources provided, affecting users who require extensive computational power.
  • Subscription Costs
    While there is a free tier, advanced features and increased resource limits come at a subscription cost, which might be a consideration for students or hobbyists.
  • Learning Curve for Advanced Features
    While basic functionality is user-friendly, mastering the more advanced features and integrations may require a learning curve, especially for users new to data science tools.
  • Dependency on External Infrastructure
    The performance and availability of Deepnote can be affected by issues with their cloud service providers, which adds a layer of dependency on external infrastructure.

Analysis of Apollo.io

Overall verdict

  • Apollo.io is generally well-regarded in its space, especially for businesses looking to enhance their sales intelligence and outreach processes. Most users appreciate its robust feature set and user-friendly interface.

Why this product is good

  • Apollo.io is considered good by many users because it provides a comprehensive sales engagement platform with features like a vast and accurate database of contacts, powerful searching and filtering tools, and automated outreach capabilities. It helps sales teams improve their prospecting efficiency and effectiveness.

Recommended for

  • Sales teams looking to streamline their prospecting efforts
  • Businesses seeking a reliable source of contact data
  • Organizations that want to automate and optimize their outreach campaigns
  • Companies of all sizes aiming to enhance their lead generation strategies

Analysis of Deepnote

Overall verdict

  • Deepnote is an excellent tool for data scientists, particularly those who value collaboration and need interactive, shareable notebooks. Its user-friendly interface and powerful integration capabilities make it a strong contender in the data science notebook space.

Why this product is good

  • Deepnote is a collaborative data science notebook designed to enhance productivity and simplify the data science workflow. It offers real-time collaboration, similar to Google Docs, making it easier for teams to work together efficiently. It supports various programming languages and integrates seamlessly with popular tools such as Jupyter notebooks, Git, and cloud storage services. Deepnote also provides a strong focus on data visualization and interactive dashboards, making it easier to interpret and present data insights.

Recommended for

  • Data scientists who work in teams and need a collaborative environment.
  • Professionals who require seamless integration with existing tools and cloud storage.
  • Users who prioritize interactive data visualization and interpretability.
  • Educators looking for an accessible platform to teach data science concepts.

Apollo.io videos

Free software to find email addresses - apollo.io review

More videos:

  • Review - โ€œFeature Fatigue Kills UXโ€ by Lily Chen, senior software engineer at Apollo.io

Deepnote videos

Could this be the Best Data Science Notebook? (Deepnote)

Category Popularity

0-100% (relative to Apollo.io and Deepnote)
Lead Generation
100 100%
0% 0
Data Science And Machine Learning
Sales Tools
100 100%
0% 0
Development
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 Apollo.io and Deepnote

Apollo.io Reviews

  1. michelleturner
    ยท Managing Director at Nuvoro Digital ยท
    Apollo for automated outreach

    We use Apollo with our Sales and BDR team to manage our cold outreach. The strength of the platform is the sequences and cadences that you can set up. Compared to other tools we have used in the past like Salesloft the UI is much easier to navigate. The main limitation is that the quality of data isn't as vast and often I can find prospects on Linkedin but not in Apollo.

    ๐Ÿ Competitors: SalesLoft
    ๐Ÿ‘ Pros:    Creating email sequences|Ab testing of emails|Good user experience
    ๐Ÿ‘Ž Cons:    Data quality is lacking sometimes|Onboardin process was cumbersome

Best AI Prospecting Tools for B2B Sales in 2026
What is the best AI prospecting tool for B2B sales in 2026? The best tool depends on your team's specific situation. toflow.ai is a strong fit for multi-channel outreach across email, LinkedIn, and WhatsApp, and is the only platform in this list with native MCP support for Claude and ChatGPT-based prospecting. Apollo.io is the leading option for teams needing a large contact...
Source: toflow.ai
11 Apollo.io Alternatives and Competitors 2024
FAQWhatโ€™s better than Apollo.io?What Apollo.io competitors are better for lead generation? What is Apollo.io used for?
Source: evaboot.com
Top 15+ Apollo.io Competitors & Alternatives [2024]
Unlike some other Apollo.io competitors, Reply is also great for engaging potential customers. The platform boasts multichannel outreach options and cloud calling. You can also use it to send personalized outreach, including videos created on Vidyard.
Source: www.kaspr.io
15 Best Apollo.io Alternatives to Find Verified B2B Leads (2024)
FindThatLead is affordable, with plans for individuals and small teams. If you just need the basic contact details for leads, FindThatLead is a practical alternative to look at instead of Apollo.io.

Deepnote Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Deepnote is a cloud-based data science notebook platform comparable to Jupyter Notebooks but with a focus on real-time collaboration and editing. It lets users write and run code in several programming languages, as well as include text, equations, and visualizations in a single document.
Source: lakefs.io
7 best Colab alternatives in 2023
Deepnote is a real-time collaborative notebook. It offers features like real-time collaboration, version control, and smart autocomplete. It also provides direct integrations with popular data sources like GitHub, Google Drive, and BigQuery. Its modern, intuitive interface makes it a compelling choice for both beginners and experienced data scientists.
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] โ€“ Features, pros & cons, pricing
Deepnote is a cloud-based, data science notebook platform that is similar to Jupyter Notebooks, but with a focus on collaboration and real-time editing. It allows users to write and execute code in a variety of programming languages, as well as include text, equations, and visualizations in a single document. Deepnote also has a built-in code editor and supports a wide range...
Source: noteable.io
The Best ML Notebooks And Infrastructure Tools For Data Scientists
A Jupyter-notebook enabled platform, Deepnote boasts of many advanced features. Deepnote supports real-time collaboration to discuss and debug the code. The platform will soon have functions such as versioning, code review, and reproducibility. Deepnote has intelligent features to quickly browse the code, find patterns in your data, and autocomplete code. It can integrate...

Social recommendations and mentions

Based on our record, Apollo.io should be more popular than Deepnote. It has been mentiond 69 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.

Apollo.io mentions (69)

  • Enriching Free Trial Signups: The PLG Data Stack for Turning Inbound Users Into Qualified Pipeline
    Personal email domains destroy this. Clearbit's Enrichment API returns a null company when it hits gmail.com. Apollo routes personal domains straight to a consumer bucket and skips B2B fields entirely. Even PDL's /person/enrich endpoint โ€” the most permissive of the major providers โ€” gives you around 32% hit rate on Gmail addresses versus 74% on corporate domains. I measured this across 6,200 signups for a... - Source: dev.to / 2 months ago
  • Clearbit Is Now HubSpot-Only: A 1-to-1 API Migration Map for Teams Getting Locked Out
    A few things worth flagging: PDL beats Clearbit's historical rates for US and Western European companies, but drops to ~52% match rate for Japan and South Korea specifically. Apollo underperforms on raw company matching but returns significantly more contacts per domain in Prospector-style queries than Clearbit's Prospector ever did โ€” the tradeoff is more stale titles in the result set. Hunter.io is fast and cheap... - Source: dev.to / 2 months ago
  • Auto-Enriching Your CRM on New Contact Creation: A No-Code Webhook Playbook
    One thing comparison guides consistently get wrong: Clay is not an enrichment API. It's a waterfall orchestration tool that calls People Data Labs, Apollo, Clearbit, and others in sequence for you. It's useful, but it adds 2โ€“8 seconds of latency per row in my runs and costs more per match than going direct. For a CRM webhook flow where you need sub-second enrichment calls, Clay is the wrong layer to hit first. - Source: dev.to / 3 months ago
  • How to Build an OSINT-Powered B2B Prospecting Workflow in 2026 (Without Getting Banned)
    Last year I ran the same LinkedIn Sales Navigator export through three enrichment APIs. Apollo matched 61% of the emails. Hunter.io matched 54%. An OSINT-first pipeline I'd built in n8n โ€” pulling from public sources before hitting any paid API โ€” matched 79% and cost roughly $0.003 per contact. The delta wasn't magic. It was sequence. - Source: dev.to / 3 months ago
  • LinkedIn Scraping Is Dead: 5 Legal, ToS-Safe Alternatives That Actually Work in 2026
    Despite having its LinkedIn Page removed in 2025, Apollo remains a functional enrichment and outreach platform with 275M+ contacts. The free tier includes 10,000 credits and the $49/month basic plan is the cheapest entry point for a combined enrichment-plus-sequencing workflow. Apollo's data collection methods have attracted LinkedIn's attention, but the product continues to operate. The risk I'd assign it:... - Source: dev.to / 3 months ago
View more

Deepnote mentions (34)

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What are some alternatives?

When comparing Apollo.io and Deepnote, you can also consider the following products

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

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

Lusha - Search less. Sell more.

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

Hunter.io - Find all the email addresses related to a domain

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.