“CRM database” gets used for two different things, and the two have almost nothing to do with each other. One is the shape of the data inside your CRM. The other is a product you buy contacts from. Teams that solve only one end up either with a beautifully structured CRM full of unreachable people, or a pile of accurate records in a structure that cannot hold them.
The database inside your CRM
Four objects, related properly:
Companies are the anchor, keyed on domain rather than name, because names are written six ways and domains are not. People belong to a company and can move to another without losing their history. Deals belong to a company with people attached, so one account can hold several over years. Activity attaches to any of them with a timestamp, which is what makes history readable later.
The common mistake is flattening this: one row per contact with the company as a text field. It works until someone changes jobs, you sell twice to the same account, or two reps spell a company differently. Then it stops being a database and becomes a list.
Most modern CRMs get this right by default. If you are assembling one yourself in a spreadsheet, Notion or Airtable, this structure is the part worth being deliberate about.
The database you buy from
| Source | Strongest at | Model |
|---|---|---|
 Stalar |
Verified contacts in any market, at request time | Pay per contact found |
 ZoomInfo |
US enterprise depth, org charts, intent | Custom contract, five figures |
 Cognism |
European coverage, GDPR posture, mobiles | Custom contract |
 Apollo |
Self-serve breadth at low cost | Seats plus expiring credits |
 Clay |
Orchestrating many sources at once | Credits, needs an operator |
 Lusha |
Quick individual lookups | Credits, free tier |
ZoomInfo is the depth option for US enterprise motions, priced accordingly; the detail is in ZoomInfo alternatives and what it costs.
Cognism is the correction for European teams, built on European data with a compliance story that survives procurement.
Apollo bundles database, sequencing and dialer cheaply, with the credit maths as the catch, covered in Apollo alternatives.
Clay is not a database but a way to run many of them at once, which is powerful and assumes someone to operate it.
Every one of these sells access to a store compiled before you needed it. That store decays from day one: contacts change jobs at roughly 2 to 3 percent a month, so record freshness matters more than record count. Vendors sell on size because size is easy to print.
Stalar inverts the order. Rather than buying access to a static file, you describe your market and agents map it, find the right person at each company and verify their email and mobile at that moment, in the local language, priced per contact found. Coverage is built per market rather than browsed, which matters most where static databases are thinnest. Those contacts land in a workspace where a sales brain records every prospect, conversation and touchpoint, and agents keep the record current from what was actually said, so the structure and the freshness stay solved together.
Deciding
- Fix the structure first. Sourcing good data into a flat model wastes both.
- Judge sources on your own market. Run the same 100 target accounts through each candidate and count verified emails and mobiles. Ignore the total-records number.
- Ask when each record was last verified. It is the number that predicts bounce rate, and the one vendors are slowest to give.
- Decide who maintains it after the import. Our production data shows what happens when the answer is nobody.
