Sek Fook

Solana has become one of the busiest venues for trading digital assets, aiming to be the internet's capital market. The question is whether onchain markets can deliver execution that stands up next to traditional venues, and attract the capital watching from the sidelines.

That comes down to what any trading desk measures a venue on: reliable fills, tight spreads, and low fees. But measuring them means getting clean trade data, which, on Solana is surprisingly hard to get!

A DEX (decentralized exchange) is a venue where trades settle onchain rather than through a broker and a clearing house. On Solana, each DEX is deployed as its own 

: Solana's term for a smart contract, living at its own address, written by its own team.

There's no unified swap standard on Solana. Each program is built on its own framework, with its own instruction layout and event encoding.

The mechanics of how each venue prices a trade differ too. And developers update their programs, introducing new instructions, events, and fields to track.

So before you can ask about price or volume, you're maintaining a decoder for each venue and keeping it current.

This is the same problem that US equities had in the 1970s. There were dozens of venues, no common format, and no way to compare a fill on one against a fill on another. They solved it with the consolidated tape, the normalized stream that made execution analysis routine – and has run continuously since.

Goldsky's Solana DEX Trades dataset does the equivalent job.

 currently decodes swaps from seven programs:

Every row is a single swap from the trader's perspective. These columns are probably what you're most interested in:

The suffixes describe pricing mechanics. Automated market makers (AMMs) quote against a fixed formula. Concentrated liquidity market makers (CLMMs) let providers deploy capital into specific price bands instead. Pump.fun's launchpad uses dynamic bonding curves, where price moves as supply is minted. The dataset normalizes all of them into the same row shape.

With Turbo, getting Solana DEX trades into your own ClickHouse is a single pipeline definition. Turbo creates the tables automatically with a 

 engine. It deduplicates on the primary key, so replays and chain reorganizations resolve to one row per swap rather than accumulating duplicates:

With all the trade data in ClickHouse, we can run price execution research on the following token pair:

Example 1: Compare execution price for the same pair across DEXes

At any given minute, what was the effective SOL/USDC price on each venue? Every row carries both sides of the trade in human units, so price is just 

. The only work is normalizing trade direction: a row can be either "bought SOL with USDC" or "bought USDC with SOL".

Example 2: Quantify the cross-venue spread (and find who's cheapest)

You can build on the same subquery to collapse the per-DEX prices into a single cross-venue spread series. This gives a direct measure of arbitrage opportunity and market efficiency. The wider and more persistent the gap, the more a naive fill costs.

Which venue is actually winning the flow? SOL-denominated volume is a clean common denominator, since the vast majority of pairs route through SOL:

Example 4: How much flow comes from aggregators vs. direct?

 makes this a one-liner. Direct swaps carry the literal string 

. Anything else is the program ID of the router that invoked the DEX. Jupiter v6, for instance, is 

JUP6LkbZbjS1jKKwapdHNy74zcZ3tLUZoi5QNyVTaV4

Solana's DEX landscape is fragmented by design. Each venue is its own program with its own quirks.

That leaves you free to focus on the questions you and your customers care about. Where's the best price? How wide is the spread? Who's winning the volume? How much flow is aggregated?

These become ordinary SQL against your own ClickHouse.

Want to reproduce any of this? The fastest way is to spin up a Solana DEX trade pipeline with Turbo pipeline above. Check out our documentation for the full schema and latest information on our Solana DEX trade datasets: 

If the DEX trade dataset you're looking for isn't listed, please contact 

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