ZoomInfo
Apollo.io
Lusha
Hunter.io
Datanyze
DiscoverOrg
Clearbit
UpLead
Python
JavaScript
Java
C++
Rust
Ruby
PHP
Elixir
ZoomInfo PythonZoomInfo makes it much easier to identify decision-makers, prioritize high-value accounts, and keep pipelies moving. With powerful AI automation and high-quality data, it's an all-in-one solution for sales, marketing, and RevOPs teams who want to save time and drive revenue growth.
As a B2B database, ZoomInfo certainly has a lot to offer. Its detailed business information on people and companies is impressive, and I've found it to be a useful resource for researching potential clients and partners.
However, I do have a few criticisms of the product. Firstly, its pricing is quite steep, especially compared to other B2B databases on the market. This makes it difficult for smaller businesses or startups to justify the cost. Additionally, while the information on ZoomInfo is generally accurate and up-to-date, I have come across a few instances where the information was incomplete or outdated.
Despite these drawbacks, ZoomInfo is still a good resource for business information. It just might not be the best option out there. If you're willing to pay for a premium service, then ZoomInfo could be worth considering. However, if you're looking for more cost-effective alternatives, there are several options to consider.
Based on our record, Python seems to be a lot more popular than ZoomInfo. While we know about 299 links to Python, we've tracked only 8 mentions of ZoomInfo. 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.
Skip ZoomInfo for this use case. It's enterprise-contract priced, built for outbound prospecting from company lists, and adds zero value for personal email resolution. Same story with Lusha โ excellent for Chrome extension-style lookups starting from a LinkedIn profile, wrong tool for an automated inbound pipeline. - Source: dev.to / about 2 months ago
Most SDR stacks start with a contact database โ ZoomInfo, Apollo, or Lusha โ and treat enrichment as a one-time step at the top of the funnel. The problem: these databases are 3โ18 months stale on average. Job titles change. Companies restructure. Decision-makers who were Director of Engineering in Q1 are VP by Q3. - Source: dev.to / 3 months ago
Kaspr is the most LinkedIn-native option on this list. The Chrome extension sits on LinkedIn profiles and exports contact data directly โ phone numbers, emails, and CRM sync. 120M+ European contacts is their differentiator; US coverage is noticeably thinner. Starting at $74/month, it's not cheap for light usage, but teams running 200+ LinkedIn outreach touches per month will find the unit economics work. Kaspr is... - Source: dev.to / 3 months ago
For the phone calls - there's a decent chance they got your number from zoominfo.com - you can go there and request to be removed. Source: about 3 years ago
I just found a few data collator sites, zoominfo.com and signalhire.com are just two - they seem to scrape sites like Linkedin etc and collate everything. Personal numbers can be found pretty easily, if you've ever signed up for a business identification number it could be there, could be in a data leak somewhere - these companies are pretty shady and will buy data from places to just get a lead. Source: over 3 years ago
137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / 2 months ago
For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / 2 months ago
Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 3 months ago
**_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โSave this dataโ - โGet this dataโ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago
Apollo.io - Apolloโs predictive prospecting, sales engagement, and actionable analytics help the teams to reach its full revenue potential.
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Lusha - Search less. Sell more.
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
Hunter.io - Find all the email addresses related to a domain
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
