How Dakota Built a Private Fund Performance Database of 18,000+ Funds

Data sourced from Joe, the private fund performance platform powered by Dakota. Learn More | Request Access

Benchmarking a fund's performance today usually means paying for access three times over: a deal-flow database with thin performance history, a benchmarking tool with narrow strategy coverage, and a manager's own marketing deck for the numbers nobody else can verify. Consultants, allocators, and GPs raising capital all pay the same tax, incomplete comparisons, stale vintages, and hours spent reconciling numbers that should already agree.

Dakota built Joe to close that gap directly: a private fund performance database with named, fund-level data on 18,000+ funds across seven asset classes, built the same way Dakota has built every core dataset since its founding, by practitioners who needed the information themselves and built the infrastructure to collect it.

In this article, we're discussing how Dakota actually built that database, where the data comes from, how it's verified, and who inside Dakota relies on it every day. By the end of this piece, you'll understand exactly what's behind the numbers on every Joe fund report.

What's Inside the Database

Joe, powered by Dakota Marketplace, brings together net and gross performance across private equity, venture capital, private credit, private real estate, infrastructure and real assets, hedge funds, and evergreen and interval vehicles, standardized so Net IRR, TVPI, DPI, and RVPI mean the same thing on every fund record. That standardization is what makes a comparison an actual comparison, instead of three providers' different definitions stitched together by hand.

Layered on top of the fund data is the context a performance number alone can't provide. Joe tracks 23,000+ general partners, including firms currently in market and fundraising, and connects 175,000+ portfolio companies back to the funds that hold them, with 1M+ private companies tracked beyond current portfolio holdings. A continuously updated set of 26,000+ private company transactions, growing by 2,000+ every month, ties fund performance to the deal activity happening around it.

How the Data Actually Gets Built

Joe’s fund and performance data is dual-sourced. One stream comes from public filings, scraped and cleaned from SEC disclosures, Form D filings, pension fund filings, and other regulatory sources. The other comes directly from manager submissions, sourced through Dakota's existing network of GP relationships, capturing performance detail that never shows up in any public filing.

Neither stream is published on its own. A 60+ person data team reviews, cleans, and verifies every record, reconciling public filings against manager-submitted data, resolving discrepancies, and standardizing formats before anything goes live. That's the difference between a research-verified database and a raw scrape: nothing in Joe is auto-populated straight from a filing or taken at face value from a manager's own submission.

The data is also continuously maintained rather than built once and left to age. The same data team relationships that source manager submissions keep the dataset current, which is the actual differentiator against providers that rely purely on public or scraped data. Their coverage goes stale the moment a fund stops filing. Joe’s doesn't.

See where a fund actually stands. Joe tracks performance on 18,000+ private funds across seven asset classes, dual-sourced and research-verified, so benchmarking a track record doesn't require three vendors and a compliance headache. Request access to see how it works.

Data Dakota's Own Teams Rely On

Joe isn't a dataset that only exists for customers. Dakota's Investment Sales team pulls the same fundraising insights, who's raising, how strategies are benchmarking, where allocator interest is shifting, to inform their own outreach. Dakota's Research team mines the same underlying data to produce the reports, fund spotlights, and market intelligence that Marketplace customers read every week.

That means the data gets used, and gets caught if something's wrong, well before an external customer would ever see a bad number. It's the same internal-first quality check Dakota Marketplace's allocator data has always run on, now applied to fund performance.

How Fund Managers and Allocators Actually Use It

In practice, that means a consultant can build a peer group from named funds instead of an anonymized cohort, filtered by strategy, vintage, geography, and fund size in any combination, then compare a target fund's IRR, TVPI, and DPI against that exact group rather than a blended median. A secondaries buyer can pull performance history on one or two specific funds tied to a transaction without buying a broad institutional subscription to answer a narrow question. A GP can trace its own fund series, Fund I through the current raise, to see whether relative performance has actually improved over time.

None of those questions can be answered well by an anonymized benchmark, or by a database priced out of reach of the firms asking them. That's the gap Joe was built to close.

See where a fund actually stands. Joe tracks performance on 18,000+ private funds across seven asset classes, dual-sourced and research-verified, so benchmarking a track record doesn't require three vendors and a compliance headache.

Request access to Joe and benchmark fund performance with data built for the comparison you're actually trying to make.