Every fund manager raising capital hits the same question early in the process: where do I find qualified LPs?
The three platforms that come up in nearly every conversation are Preqin, PitchBook, and Dakota. They all contain LP data. But they solve different problems, serve different workflows, and come at very different price points.
This guide breaks down what each platform actually does, where they overlap, and how to decide which one fits your fundraising operation.
What You’re Really Buying
Before comparing features, it helps to understand what an LP database actually gives you. At the most basic level, you’re buying three things:
- LP profiles with allocation data (what they invest in, how much, and how often)
- Contact information for investment professionals at those LP organizations
- Search and filtering so you can narrow a universe of thousands of LPs down to the ones that match your fund
The difference between platforms comes down to how deep each of those three layers goes, what additional data surrounds them, and how the platform expects you to use it.
Preqin: The Institutional LP Intelligence Standard
Preqin has been the default LP research platform in private capital for years. The company was acquired by BlackRock in 2023, which deepened its data resources.
What Preqin does well:
- Deep LP allocation data. Preqin tracks commitments, fund preferences, allocation targets, and historical investment activity across private equity, venture capital, real estate, infrastructure, and private debt.
- Institutional coverage. Preqin’s strength is pension funds, endowments, foundations, sovereign wealth funds, and insurance companies. If you’re targeting traditional institutional allocators, this is the deepest dataset available.
- Fund performance benchmarks. Beyond LP data, Preqin provides fund-level performance data that can help you position your fund relative to peers.
- Fundraising market analytics. Quarterly data on fundraising timelines, fund sizes, and LP appetite by strategy.
Where Preqin falls short:
- Family office coverage is thinner than institutional. If your LP target list is heavy on family offices, Preqin’s coverage may leave gaps.
- The interface has historically been functional rather than intuitive. Preqin has been investing in UX improvements, but the platform still has a learning curve.
- Pricing puts it out of reach for many emerging managers.
Pricing range: Preqin subscriptions typically start in the range of $15,000-$20,000/year for basic access and can exceed $50,000/year for full platform access including performance data and custom analytics. Pricing varies based on modules selected and organization size.
PitchBook: The Broadest Dataset
PitchBook, owned by Morningstar, is a financial data platform that covers private and public markets. LP data is one module within a much larger product.
What PitchBook does well:
- Breadth of data. PitchBook covers companies, deals, funds, LPs, advisors, and service providers across the entire private capital ecosystem. If you need to research a potential LP’s portfolio companies, recent exits, or co-investment activity, PitchBook connects those dots.
- Company and deal data. Beyond LP profiles, PitchBook gives you deep visibility into portfolio companies, valuations, and transaction history. This is useful for managers who want to understand what their target LPs are already exposed to.
- News and activity tracking. PitchBook surfaces recent news, personnel changes, and fund launches, which helps keep your LP outreach timely.
Where PitchBook falls short:
- The platform is built for the broader financial research market, not specifically for fundraising. LP search and filtering exist but aren’t as fundraising-workflow-oriented as Preqin.
- Cost is high, and much of what you’re paying for (company data, deal data, public market coverage) may not be relevant if your primary need is LP targeting.
- LP allocation data, while available, doesn’t always match the depth of Preqin’s commitment-level tracking for institutional investors.
Pricing range: PitchBook subscriptions generally fall in the $20,000-$50,000+/year range depending on the number of seats and modules. Academic and smaller-firm pricing may be available at lower tiers.
Dakota: The Relationship-First Alternative
Dakota approaches the LP database problem differently. Rather than building the largest possible dataset, Dakota focuses on LP relationships and fundraising-specific workflows.
What Dakota does well:
- LP Marketplace. Dakota’s marketplace model allows LPs to signal interest in specific strategies and fund types. This creates a pool of LPs who are actively looking to allocate, rather than a static database of contact records.
- Fundraising workflow. Dakota is designed around how fund managers actually raise capital: tracking LP interactions, managing a fundraising pipeline, and coordinating meetings. The database is embedded in a CRM-like workflow.
- Accessibility for emerging managers. Dakota’s pricing is generally more accessible than Preqin or PitchBook, which matters when you’re a first-time manager watching every dollar.
- LP-sourced data. Because LPs opt into Dakota’s marketplace, the contact data can be more current than data scraped or researched by third parties.
Where Dakota falls short:
- The total LP universe is smaller than Preqin or PitchBook. Dakota is growing its database, but if you need comprehensive global institutional coverage, it may not be sufficient as a standalone tool.
- Less depth on fund performance benchmarks and market analytics compared to Preqin.
- International coverage, particularly in Asia and the Middle East, is more limited.
Pricing range: Dakota’s pricing is generally in the $5,000-$15,000/year range depending on the plan, making it the most accessible of the three for smaller firms.
Head-to-Head Comparison
| Feature | Preqin | PitchBook | Dakota |
|---|---|---|---|
| LP database depth | Deep institutional coverage | Broad but less allocation-specific | Growing, marketplace-driven |
| Family office coverage | Moderate | Moderate | Moderate-to-good (marketplace model) |
| Fund performance data | Yes, extensive | Yes | Limited |
| Company/deal data | Limited | Extensive | No |
| Fundraising workflow tools | Basic | Basic | Built-in CRM-style pipeline |
| LP intent signals | No | No | Yes (marketplace opt-in) |
| Typical pricing | $15K-$50K+/yr | $20K-$50K+/yr | $5K-$15K/yr |
| Best for | Institutional LP targeting | Broad market research + LP data | Relationship-driven fundraising |
How to Decide
The right choice depends on where you are in your fundraising lifecycle and who you’re targeting.
Choose Preqin if: You’re raising from institutional LPs (pensions, endowments, foundations, insurance companies) and need deep allocation data to qualify targets. You have the budget, and your primary workflow is LP research and targeting.
Choose PitchBook if: You need LP data alongside broader market intelligence. If you’re also tracking competitive funds, portfolio company data, or deal flow, PitchBook gives you one platform for multiple research needs.
Choose Dakota if: You’re an emerging manager focused on building LP relationships efficiently. You want a fundraising-oriented workflow, you value LP intent signals, and you need to keep costs manageable during your first raise.
The practical reality: Many fund managers don’t choose just one. A common approach is to start with Dakota for its workflow tools and marketplace access, then add Preqin for institutional LP research when the fundraise requires deeper targeting. PitchBook tends to get layered in when a firm grows into a multi-fund platform or needs the broader market data for deal sourcing alongside capital raising.
What an LP Database Won’t Do for You
No database replaces the work of actually building LP relationships. The managers who raise capital efficiently use these tools to be more targeted and better prepared, not to send more emails.
An LP database helps you understand which investors are allocating to your strategy, how much they typically commit, and what their portfolio already looks like. That intelligence should make every conversation more relevant. But the conversation itself still has to happen, and it still has to be good.
The best use of any LP database is to shrink your universe from “every LP in the world” to “the 200 LPs who are most likely to write a check for this specific fund.” For a broader look at how LP data fits into investor outreach and the overall fund marketing process, we cover those frameworks separately. Our LP Discovery Playbook walks through how to build that targeting strategy step by step. Everything after that is execution, and a structured institutional investor outreach framework ensures those conversations actually happen.
Emerging managers with limited budgets should start with Dakota for relationship-driven access, graduate to Preqin for institutional LP intelligence, and consider PitchBook when they need broader deal and company data alongside investor research.
Frequently Asked Questions
Which LP database is best for first-time fund managers?
Dakota is often the most accessible starting point for first-time managers. Its pricing is lower than Preqin or PitchBook, and the platform is specifically designed around LP relationships and fundraising workflows rather than broad financial data. That said, managers targeting large institutional LPs may need the depth of Preqin's allocation and commitment data.
Can I use Preqin or PitchBook data for cold outreach to LPs?
Technically yes, but this is generally not effective. Institutional LPs receive hundreds of cold emails per month. The real value of these databases is qualifying which LPs are actually allocating to your strategy, understanding their existing portfolio, and identifying warm introduction paths. The data should inform your targeting, not replace relationship-building.
How often is LP data updated in these platforms?
Preqin and PitchBook both update their databases continuously, though the freshness of specific LP records varies. Contact information can go stale quickly as investment professionals move between firms. Dakota's model includes a marketplace component where LPs opt in, which can result in more current contact data for participating investors.
Do I need an LP database if I already have a placement agent?
Most placement agents use their own LP databases and relationships, so there is overlap. However, having your own database access gives you independent visibility into your market, helps you evaluate your placement agent's coverage, and positions you for future raises where you may not use an agent.
