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Guide

M&A Database: How to Access Mergers & Acquisitions Data

What is an M&A database and how do you get mergers-and-acquisitions data affordably? A guide to acquisition data — acquirers, targets, deal value and type — plus 200K+ deals on Acquirezy.

Acquirezy8 min read

The short answer

An M&A database is a structured, searchable record of mergers and acquisitions — acquirer, target, date, disclosed value and deal type. Enterprise M&A data is usually expensive and quote-based; Acquirezy offers 200K+ acquisitions plus a PE M&A workspace, searchable and filterable, from $9/month — with CSV export and whole-dataset licensing.

Whether you're tracking a serial acquirer, sizing a sector's consolidation, or building an M&A target list, you need the deals in a structured, queryable form — not scattered across press releases. This guide explains what an M&A database is, what's in it, where to get one, and how to access acquisition data affordably.

What is an M&A database?

A mergers-and-acquisitions (M&A) database is a collection of acquisition transactions stored as structured records you can search, filter and analyse. Instead of reading individual announcements, you can answer questions like "which firms acquired the most healthcare companies last year?" or "how many software deals happened in 2025?" in seconds.

What's in acquisition data

A good M&A record includes:

  • Acquirer — the buying company (with its own profile).
  • Target — the company being acquired.
  • Announced date — when the deal was made public.
  • Disclosed value — the deal price, where disclosed.
  • Deal type — acquisition, merger, majority stake, and so on.
  • Sector & geography — for filtering and market analysis.

The real power comes from connecting those records to company profiles, funding history and investors — so a deal isn't a dead end but a doorway into the wider graph.

Where to get M&A data

M&A data sources
SourceStructured & searchable?Cost
AcquirezyYes — 200K+ deals + PE workspaceFree to browse; $9–$29/mo; bulk licensing
Enterprise deal platformsYes, very deepEnterprise, quote-based (high)
Regulatory filings / pressNo — unstructuredFree but manual

Acquirezy's M&A data

Acquirezy includes 200K+ acquisitions with acquirer, target, announced date, disclosed price and deal type — filterable by company, sector, year and deal size. Every acquirer and target links to a full company profile with its funding, investors and people. On the Intelligence plan, a dedicated PE M&A intelligence workspace lets you slice deals by private-equity firm, sector, year and size. You can also ask Chase AI questions like "compare the top acquirers in fintech" and get grounded answers.

What 203K acquisitions reveal

Here's something you can only see with a structured M&A database — and it surprises most people. The most acquisitive companies in the world aren't the tech giants; they're insurance consolidators and private-equity firms. These are the top serial acquirers by number of deals in Acquirezy's data (September 2026):

Top serial acquirers by deal count
AcquirerTypeAcquisitions
GallagherInsurance brokerage524
HUB InternationalInsurance brokerage406
AccentureConsulting349
CVC Capital PartnersPrivate equity266
GoogleTechnology254
Riverside CompanyPrivate equity248
EQTPrivate equity240
MicrosoftTechnology239
Advent InternationalPrivate equity234
Assured PartnersInsurance brokerage233

Insurance brokers (Gallagher, HUB, Assured Partners) and PE roll-up specialists dominate — Gallagher alone has made 524 acquisitions. That's the kind of pattern a structured database surfaces instantly and a pile of press releases never will.

Deal activity by sector and year

Acquisitions cluster in a handful of sectors — Software (31,637 deals), Manufacturing (27,921), Information Technology (23,641) and Health Care (18,086) lead — and deal volume has held around 12,000–16,000 announced deals a year recently (2023: 12,101, 2024: 15,578, 2025: 15,752). Being able to slice deals this way — by acquirer, sector and year — is the whole point of an M&A database.

How teams use an M&A database

  • Corporate development — track acquirers, benchmark deal activity, build target lists.
  • Private equity & VC — map consolidation, find add-on targets, source deals.
  • Investment bankers & advisors — research comparables and buyer universes.
  • Founders — understand who's acquiring in their space and at what valuations.

Explore 200K+ acquisitions

Search and filter M&A deals by acquirer, sector, year and size — connected to company, funding and investor data. Free to browse; Pro from $9/mo.

Comparing platforms? See Acquirezy vs PitchBook and Acquirezy vs LSEG for how the M&A data stacks up on price and access.

Frequently asked questions

What is an M&A database?

An M&A database is a structured collection of mergers-and-acquisitions transactions — each record typically includes the acquirer, the target, the announced date, the disclosed deal value and the deal type. It lets you search, filter and analyse acquisition activity by company, sector, geography, year or deal size.

Where can I find M&A data?

Options range from free public sources (regulatory filings, press releases) to enterprise providers. Acquirezy offers 200K+ acquisitions with acquirer, target, date, disclosed price and type — searchable and filterable — plus a PE M&A intelligence workspace, from $9/month.

Is there a free M&A database?

You can browse acquisitions on Acquirezy's Free plan (deal records are visible; disclosed prices and some fields unlock on paid plans). Fully free public sources exist (filings, news) but aren't searchable as a structured database.

How much does M&A data cost?

Enterprise M&A data platforms are typically expensive, quote-based contracts. Acquirezy is transparent and self-serve: Free to browse, $9/month Pro and $29/month Intelligence, with whole-dataset licensing available via Bulk Dataset Export.

Can I export M&A data or get it via API?

Yes. Paid plans include CSV export, and Bulk Dataset Export licenses the whole acquisitions dataset as CSV, JSON, JSONL or Parquet delivered via API, S3, GCS or SFTP.

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