On-chain behemoth war: Who will control the flow of value and become the new oligopoly in the Web3 industry?

Written by: Saurabh Deshpande, Decentralised.co

Compiled by: AididiaoJP, Foresight News

In November 2023, Blackstone Group acquired a pet care app called Rover. Rover was originally just used for finding people to walk dogs or look after cats. The pet care industry typically consists of tens of thousands of small, mostly localized, and offline service providers. Rover integrates these suppliers into a searchable marketplace, adding review and payment features, making it the default platform for pet care services. By the time Blackstone privatizes it in 2024, Rover has become the hub of demand in this field. Pet owners think of Rover first, and service providers have no choice but to list on this platform.

ZipRecruiter has done something similar in the recruitment field. It collects job information from employers, job boards, and applicant tracking systems and distributes it across multiple channels. ZipRecruiter posts job openings on social networks like Facebook. For employers, ZipRecruiter becomes a one-stop distribution channel; for job seekers, it is a unified entry point to the market. ZipRecruiter does not own companies or positions, but rather the relationships with both parties. Once this relationship is solidified, it can charge for visibility and job matching, which is an introductory lesson in aggregation economics.

Aswath Damodaran refers to this model as "shelf ownership": consolidating chaotic and decentralized supplies, controlling their display, and charging for access. Ben Thompson calls it the "aggregation theory": establishing direct relationships with end users, allowing suppliers to compete to serve them, and extracting value from each transaction. The core characteristics across different fields are consistent: Google with web pages, Airbnb with listings, Amazon with products.

The Amazon flywheel is a classic interpretation of this concept. During the recession that followed the burst of the internet bubble, Jeff Bezos and his team borrowed the "flywheel" concept from Jim Collins, illustrating a cycle that every MBA can now recite: more choices lead to a better customer experience, attracting more traffic, which in turn attracts more sellers, reducing unit cost structure, thereby providing lower prices, ultimately resulting in more choices. The effect of turning the flywheel once is limited, but after turning it a thousand times, the machine begins to roar. Bezos's motto during this period was: "Your profit is my opportunity." Its core lies in self-reinforcement: more users, more suppliers, lower costs, ultimately achieving higher profits.

Once this model takes effect, it can be considered perfect. The growth rate of costs is far lower than that of revenue, and products will be optimized as the number of users increases. However, it only holds true under two conditions: the aggregated content must have value, and the suppliers must find it difficult to exit easily; both are essential, otherwise the moat will become shallow. Taking eBay as an example, it aggregated millions of unique niche sellers and buyers in the early 21st century. This aggregation was once highly valuable, but when sellers realized they could build their own stores on Shopify or switch to Amazon, they all began to leave. The flywheel does not stop turning overnight, but if the suppliers are no longer controlled, it begins to wobble, ultimately becoming ordinary.

Damodaran explains the power of platforms and aggregators in a concrete way. He mentions "controlling the shelf," which does not refer to supermarket shelves in the literal sense, but rather to the space that customers first come into contact with when demand arises. Controlling this space means deciding what content is displayed, how it is displayed, and the cost of entry. You do not need to own the products themselves, just the relationship with the buyers; others must go through you to reach the buyers. In analyzing Instacart, Uber, Airbnb, or Zomato, Damodaran repeatedly emphasizes that the task of the aggregator is to consolidate a chaotic, fragmented market into a single glass window and to make that glass window the only one worth paying attention to. Once this is achieved, you can charge for the "viewing rights."

Ben Thompson believes that aggregators are a type of business that establishes direct relationships with end users at internet scale, providing a standardized and reliable experience while allowing suppliers to compete to serve them. At internet scale, you are not the biggest store in town, but rather a store that covers all towns simultaneously.

The marginal cost of serving the next customer is almost zero, but the marginal value of having them is enormous. Each customer reinforces your brand, data, and network effects. As aggregators control demand, suppliers become interchangeable. This does not mean there is no difference in quality, but rather that suppliers cannot take customer relationships with them when they leave. Hotels on Expedia, drivers on Uber, and sellers on Amazon all need each other more than they need the aggregator.

Damodaran's research reminds us that flywheels do not operate the same way in all markets. For example, Uber aggregates local driver liquidity, but drivers can open three apps simultaneously and choose the first order they receive. This creates vulnerabilities in the moat. In contrast, Airbnb hosts offer unique listings with limited alternative channels, making their commissions more sustainable.

In areas with lower profit margins, shelves may have value, but the space for commissions is limited, and suppliers are prone to rebound. This is why Instacart must venture into advertising and white-label logistics to achieve growth.

The economic structure of supply is just as important as the number of users on the platform. If the goods are readily available within the platform, you are merely a convenience store with better visibility; however, if the content is scarce, differentiated, and difficult to substitute, people will continue to visit, even if you charge higher fees. Think of high-end listings on Airbnb.

Why did the aggregator fail?

When conditions are missing, the aggregator is no longer a flywheel, but just a costly carousel.

Quibi is a typical case of failing to control the shelf. The platform has expensive Hollywood content and a beautifully designed app, yet lacks direct channels to reach users. Potential users have already gathered on YouTube, Instagram, and TikTok. These platforms capture attention, while Quibi locks its content in a standalone app, away from users, leading it to rely solely on ads and promotions to attract users.

An excellent aggregator starts with a zero marginal cost user outreach method, such as built-in distribution, installation volume, or daily habits. Quibi had nothing and ultimately exhausted its time and funds before building these.

Facebook's Instant Articles also faces similar issues. Its concept is to aggregate content from publishers, accelerate loading within Facebook, and monetize traffic. However, publishers can easily distribute content to their open networks, apps, or other social platforms. Instant Articles has never become the default reading platform; it is just one option in the information stream.

Both examples violate the same rule: the enterprise fails to have a user relationship in a way that creates default behavior, and the supplier will not be significantly harmed after exiting.

The list of excellent aggregators is simple:

Directly connect and own user relationships;

The supplier must be either unique or interchangeable so as not to be held hostage by a single supplier.

The marginal cost of increasing supply is close to zero or low enough to optimize the business model with scale.

If these conditions are not met, you are just another easily replaceable intermediary.

How liquidity becomes a moat

In the crypto industry, projects can build moats in different ways. Some establish trust through licenses and regulation (such as USDC), some rely on technology (like Starkware's proof systems or Solana's parallel execution), and others depend on community and network effects (like Farcaster's user graph). However, the hardest to shake is liquidity.

"Proper execution" is crucial. However, if the incentives are strong enough, liquidity will shift rapidly. In 2020, Sushiswap siphoned over $1 billion in funds from Uniswap within days through liquidity mining rewards. The lesson is simple: liquidity will only be stable when leaving is more painful than staying.

Hyperliquid is well-versed in this path. It not only builds the deepest order book for perpetual contract exchanges but also allows other applications and wallets to directly access its liquidity. For example, Phantom can tap into Hyperliquid's order flow, providing users with narrow spreads without the need to build their own market. In this model, aggregators need suppliers even more. When traders and applications default to your routing, you are no longer an ordinary aggregator but a core channel they cannot avoid.

In addition to its own platform, Hyperliquid processed over $13 billion in transaction volume through other builders last month. Phantom handled $3 billion in transaction volume through its routing, earning over $1.5 million. This demonstrates Hyperliquid's strong current network effects.

Liquidity allows you to convert assets without affecting the price. In the financial and DeFi sectors, deep liquidity makes trading cheaper, borrowing safer, and derivatives possible. A lack of liquidity can turn even the most perfect protocol into a ghost town. Once successfully established, liquidity tends to persist. Traders and applications will gravitate towards deep pools, further increasing liquidity, narrowing spreads, and attracting more trades.

This is the reason why protocols like Aave continue to thrive. Aave has large-scale lending pools of various assets, making it the preferred choice for borrowers and lenders seeking scale and security. As of August 6, the total locked value of Aave across chains exceeded $24 billion. In the past 12 months, borrowers paid $640 million in fees, and the platform's revenue was approximately $110 million.

The aggregator Jupiter, also based on Solana, has evolved from a routing tool to the default entry point for transactions on the network. On Ethereum, Uniswap has centralized most of the spot liquidity, so aggregators like 1inch can only provide marginal improvements. However, on Solana, liquidity is dispersed across platforms like Orca, Raydium, and Serum. Jupiter consolidates this into a single routing layer, always offering the best prices. Its trading volume once accounted for nearly half of the total computational usage of Solana, and any delays or interruptions would immediately affect the execution quality across the network.

Viewing liquidity as an aggregated object makes Jupiter's product decisions easier to understand. Acquisitions, mobile applications, and expansion into new trading and lending products are all aimed at capturing more order flow, maintaining liquidity through Jupiter routing, and consolidating its position.

Jupiter is worth paying attention to because it is a clear case of evolving from a niche tool to a liquidity platform in DeFi. It started with the search for the best spot prices and gradually became the default route for Solana liquidity, subsequently expanding to attract entirely new liquidity products. Observe how it navigates through these stages and reinforces each other, providing a vivid example for aggregating dynamics.

Aggregated Layers

The three questions are a quick checklist for identifying potential aggregators:

What are the key differentiating factors for existing enterprises? Can they be digitized? In DeFi, the differentiating factor is liquidity. Deep pools can provide narrower spreads and safer loans. Liquidity has already been digitized, making it easy to read and compare.

If differentiated factors are digitized, will competition shift towards user experience? When liquidity can be accessed arbitrarily, competition revolves around execution quality: faster settlement, better routing, and fewer failed transactions. Products like BasedApp and Lootbase were born from this. The former encapsulates DeFi primitives into a smooth mobile experience, while the latter brings Hyperliquid's deep perpetual liquidity to mobile.

If we win the user experience, can we build a virtuous cycle? Traders come for better prices, attracting more liquidity, which in turn offers better prices. When liquidity becomes ingrained as a habit and integrated, it becomes sticky.

Become the default entry point of the market, and if the suppliers cannot bear your absence, you can collect display fees or decide the order flow in DeFi.

Note: The boundaries between different levels are often blurred. Classification is not precise, but rather provides a thinking model for aggregation levels.

First level: price discovery

This is the most basic job: telling people where the best trades are. Kayak is for flights, Trivago is for hotels. In the crypto space, early DEX aggregators like 1inch or Matcha fall into this category. They check available pools, display the best exchange rates, and provide jump-in access. Price discovery is useful but fragile, and the exchange function of DeFiLlama is the same.

If the underlying market is already centralized (such as Ethereum spot trading on Uniswap), the improvement of routing is minimal, and users can go directly to the trading venue; the help you provide is not essential.

Second Level: Execution

At this point, you no longer direct users elsewhere, but instead operate on their behalf. Amazon's "one-click purchase" belongs to this level. In DeFi, Aave's lending function is at this level. When borrowing, liquidity is already present in its contract. Execution increases stickiness because the results are directly related to you: quick settlement and a good experience with no failed transactions.

Level Three: Distribution Control

You become the entry point. Google Search for web pages and app stores for mobile applications fall into this category. In the crypto space, the exchange label built into wallets can serve as the starting and ending point for ordinary users.

On Solana, Jupiter has reached this level. It started as a price discovery tool, entering the execution layer through smart order routing, and then embedded in front-ends like Phantom and Drift. A large number of Solana transactions are actually Jupiter transactions, even if users have never entered "jup.ag". This is distribution control, where the supplier cannot bypass you to reach the users.

Climbing the hierarchy in DeFi

The challenge of DeFi lies in the potential for rapid shifts in liquidity. Incentives can drain a liquidity pool overnight. Therefore, moving from the first tier to the third tier is not only about becoming a top aggregator, but also about creating sufficient reasons for liquidity and order flow to continuously pass through your routing.

On Ethereum, 1inch mainly stays at the second level, as Uniswap has completed the aggregation work through concentrated liquidity. Routing for edge cases is still valuable, but improvements are limited, and many traders choose to skip it. Additionally, aggregators like CowSwap and KyberSwap also hold a considerable share. Aave belongs to the second level, as it dominates execution in its niche, but it is infrastructure rather than a starting point.

The advantage of Jupiter on Solana lies in its ability to ascend through three levels. Liquidity is dispersed, with the first level holding significant value; the routing engine outperforms manual exchanges, naturally transitioning to the second level; by directly integrating wallets and dApps, it reaches the third level, fully controlling the distribution of Solana's liquidity. At one point, nearly half of Solana's computation came from Jupiter transactions, as both the demand side from traders and the supply side from liquidity pools rely on Jupiter.

After reaching the third level, the question becomes "What else can be run through this distribution?" Amazon started with books and ended with everything; Google began with search and ultimately took control of maps, emails, and cloud computing. For Jupiter, distribution is the order flow. The obvious next step is to add products such as perpetual contracts, lending, and portfolio tracking, utilizing the same liquidity relationships.

A bigger move is Jupnet. Solana has yet to match the throughput and execution characteristics of venues like Hyperliquid, which are designed for financial-grade latency and determinism. These characteristics are crucial for scaling the entire financial stack to real-world sizes. A simpler option would be to launch products on chains that already possess these features, but Jupiter has chosen the more difficult path of building Jupnet as an application-controlled low-latency execution layer, running in parallel with Solana.

Jupnet aims to become a shared infrastructure within the Solana ecosystem, supporting latency-sensitive transactions such as perpetual contracts, quote request systems, and batch auctions, with the ultimate native settlement on Solana. If successful, it will provide the expected speed and certainty of a vertically integrated venue while maintaining user and asset retention. This is an attempt to bridge the gap between the throughput of general-purpose blockchains and the global financial micro-latency demands, without the need for cross-chain liquidity fragmentation.

However, it should be noted that despite Jupiter's dominance within Solana, the industry still faces fierce competition. In the cross-chain space, 1inch, CoWSwap, and OKX Swap maintain significant positions. By 2025, Jupiter is expected to average around 55% market share among the top five DEX aggregators, but this share fluctuates with on-chain activity and integrations. The chart below shows the degree of decentralization of aggregation layers outside of Solana.

Clearly, Jupiter has become an aggregator in the Solana ecosystem. The flywheel has been set in motion: more traders bring more liquidity, more liquidity optimizes execution, and better execution attracts more traders. At this point, you are not just a liquidity aggregator, but also a shelf, a habit, and an entry point to the market. So, when liquidity is no longer sufficient, how do you continue to grow? Jupiter's answer is to acquire projects that have taken control of new user flows.

Mergers and acquisitions as a growth engine

Previously, I wrote an article exploring two major themes of corporate scaling: the essence of disruptive innovation and how companies can accelerate this process through mergers and acquisitions. The former relates to building new products, features, or capabilities based on existing advantages, while the latter concerns identifying when "buying" is a faster way to establish an advantage than "building".

The evolution of Jupiter combines both. Its acquisition strategy is rooted in seeking founder teams with real appeal and integrating them into a distribution network that amplifies impact. The company looks for expert teams in vertical fields to expand coverage without burdening the core roadmap.

This is not just about purchasing functional overlays, but rather acquiring teams that have already dominated the target market segments of Jupiter. When these teams access Jupiter's distribution wallet interface, API, and routing, their product growth accelerates, and the generated traffic feeds back into Jupiter's core.

Moonshot brings a token launchpad that transforms new token creation into direct exchange and trading activities within the Jupiter ecosystem; DRiP adds a community-driven NFT minting and distribution platform, attracting audiences away from trading interfaces and converting them into on-chain behavior; Portfolio acquisition provides active traders with position management tools. Jupiter could have built these features internally at a lower cost, but its goal is to acquire founders, not just functionality.

However, the growth of some indicators has yet to materialize. Taking the launchpad sector as an example, market leaders Pumpdotfun and LetsBonk control over 80% of daily token issuance, while Jup Studio and Moonshot together account for less than 10%. The chart below shows the dominance of the incumbents. In this situation, the default pattern may have already been solidified, and Jupiter may need a completely different approach to break through.

Power Amplifier: Founder-led Mergers and Acquisitions

To broaden the shelf, it is necessary to introduce operators who have mastered the targeted market segmentation. Jupiter's selection criteria are: does the team bring new liquidity or users that strengthen the flywheel? This logic echoes Amazon's early flywheel: each addition of a category or supplier expands "selection," optimizes the customer experience, drives more traffic, and subsequently attracts more suppliers.

For Jupiter, each acquisition is like adding new shelves to a store, expanding choices and deepening the connection between traders and liquidity providers.

Acquiring creative founders allows Jupiter to penetrate unfamiliar fields (such as the NFT culture of DRiP or mass retail token issuance) while not diluting its core competitiveness. These founders understand the niche markets, have communities that trust them, and can act quickly. Accessing Jupiter's distribution channels amplifies its reach overnight, while Jupiter gains new user flow and liquidity.

Acquisition cases reflect this: Moonshot is a minting and trading platform aimed at mainstream behavior, whose issued tokens can be seamlessly transferred into the exchange, funding market, and perpetual contracts within the Jupiter ecosystem; DRiP is a creator-first collectibles distribution channel that attracts communities that previously did not engage with trading interfaces.

Moonshot added over 250,000 users within three days of the launch of the TRUMP token, processing over $1.5 billion in transaction volume; DRiP attracted over 2 million collectors, minting over 200 million collectibles, with secondary sales exceeding 6 million transactions.

Integration follows a clear model: the founders retain control over product direction; the product is launched with access to the Jupiter interface and backend, benefiting instantly from its user base, while Jupiter gains new traffic; each acquisition adds unique liquidity primitives (such as issuance, culture, leverage), rather than duplicating existing features. Core competitiveness remains unchanged, and all paths still return to Jupiter.

In DeFi, code can fork overnight, but market share is hard to replicate. The founder-led mergers and acquisitions allow Jupiter to gain market share without losing its core path, making its flywheel harder to replicate. As application control execution and low-latency infrastructure mature, Jupiter may target teams such as risk engines, matching layers, and professional venues, integrating them into Jupnet.

Aggregator vs Supplier

Overall, two dominant models are emerging in DeFi: Jupiter and Hyperliquid. Both are powerful, but their strategies are completely different.

Hyperliquid aims to control liquidity rather than directly owning end-user relationships. It provides liquidity as a service. If a better user experience can be built, you are welcome to use Hyperliquid's order book and execution engine. Builder Codes are based on this concept, allowing others to own the front-end experience while Hyperliquid quietly supports the back end, which is a vendor-first model.

Jupiter focuses on distribution, hoping to have interfaces, shelves, and market entrances, becoming the default interface to aggregate dispersed liquidity and direct it where needed. This means controlling user relationships, not just executing transactions. From perpetual contracts to portfolios, Jupiter aims to ensure that all financial interfaces begin and end within its ecosystem.

However, perpetual contracts may expose the current limitations of this strategy the most. Jupiter has made progress on Solana, but Hyperliquid still dominates the market with about 75% of the perpetual DEX market share. The chart below shows the lead margin of Hyperliquid in terms of original trading volume:

Both modes bet on the scale, but start from opposite ends. Jupiter believes that liquidity follows the user interface; Hyperliquid believes that liquidity is the interface. Jupiter builds the entry, while Hyperliquid builds the endpoint.

In practice, we witness differentiation: if a broad interface and user aggregation are needed, choose Jupiter; if depth, certainty, and composability are required, choose Hyperliquid. One side transforms liquidity into a reliance network, while the other becomes the underlying structure built by the crowd.

The winner is not only the first to arrive but also the one that others cannot give up.

This is exactly what makes DeFi exciting right now. We are witnessing a philosophical showdown for the first time: one side believes distribution is the moat, while the other firmly believes liquidity is.

Application is a new platform

When Ethereum Layer 2 first emerged, people hoped it would become a new platform: a neutral ground where applications could be composable, competitive, and scalable. However, it turned out that L2 did not become the platform as imagined, but rather remained at the infrastructure level: providing the technological foundations for speed, security, and scalability, yet failing to control user relationships.

The platform is the interface at the starting point of the user journey, where demands are aggregated, habits are formed, and distribution survives. Few L2s cross this line; most are pipelines rather than shelves, rarely constructing meaningful distribution, and even less often becoming the default entry point for users.

On the contrary, applications like Jupiter and Hyperliquid are gradually revealing platform characteristics. They have user relationships, embed into daily habits, and strengthen their positions through acquisitions or integrations with other applications. In fact, they are starting to resemble Web2.

Google goes beyond search engines, acquiring YouTube to transform its search advantage into video dominance; Facebook expands its control over attention by acquiring Instagram and WhatsApp. They target adjacent fields where they are absent but users have already congregated, and the key is to acquire the core players in these fields. Once acquired, these applications can immediately tap into the existing distribution flywheel of Google and Facebook, resulting in the capture of multi-channel user attention.

Jupiter is currently running a similar strategy. The launchpad, NFT minting tools, portfolio managers, and now Jupnet all serve the same purpose: to expand coverage, capture more user behavior, and route more liquidity to itself. Its strategy is to become the shelf, the default choice, and the starting point for financial interactions.

However, aggregation is not a guaranteed strategy for success. History is filled with failed platform acquisitions and aggregation attempts, either due to a lack of user relationships or a misunderstanding of how habits are formed.

Taking Microsoft's acquisition of Nokia as an example. This is a bet on controlling mobile distribution, but users have turned to the iOS and Android ecosystems. Microsoft has hardware and software, but its mobile devices and operating systems are either too similar to existing products or not compelling enough to prompt user switch. It has not controlled the application layer, failed to win developer loyalty, and did not provide reasons for behavioral change. The lack of control over supply or clear differentiation has led to the products being ignored.

These cases reflect the core truth: acquisitions do not create a flywheel by themselves. Without a starting point, habits, or interfaces, no matter how many features are bundled, users will not follow.

This makes DeFi particularly interesting at the moment. Jupiter acquires front-end, distribution channels, and liquidity primitives, trying to become the default entry point for the Solana financial stack; Hyperliquid does the opposite: building depth rather than breadth, allowing others to build around its portfolio.

In a sense, we are witnessing a real platform war unfolding between applications, rather than between public chains as many have anticipated. This raises a bigger question: if L2 does not control distribution, where will the value flow when the applications on it are in control? What about the fat protocol?

We conclude with unresolved issues, as there are no definite conclusions yet. In the future, we will bring sharper perspectives, new data points, and more stories and analogies to clarify the direction of all this.