Real-time blockchain infrastructure is often discussed as a transport problem.
How quickly can an event travel from a validator to an application?
For many Solana systems, that is only half the story.
Once the event reaches the client, the application still has to understand it. Depending on the source, that can mean protobuf decoding, Borsh decoding, instruction parsing, account-index resolution, token conversions and protocol-specific interpretation.
So a second architectural question appears: should data be decoded inside the application, or before it reaches the application?
There are good reasons for both approaches.
The Case for Raw Data
Raw data gives the development team maximum control.
A team may prefer raw Yellowstone-compatible protobuf streams because it wants to support custom programs, use proprietary decoding logic, preserve every field, independently verify interpretation, optimise its own parser or avoid dependence on a provider’s normalised schema.
This is particularly attractive for infrastructure companies, indexers and teams whose parsing logic is part of their intellectual property.
Raw data is also more future-proof when the provider does not yet support a newly launched program.
The Cost of Client-Side Decoding
Control comes with engineering work.
A typical real-time pipeline may look like:
gRPC message
↓
protobuf decode
↓
transaction/account extraction
↓
program identification
↓
Borsh or custom decode
↓
normalise fields
↓
strategy / application logic
Every stage consumes CPU and adds code that must be tested and maintained.
For a high-throughput indexer, that may be expected.
For a trading bot reacting to a small number of well-known programs, much of the parsing work may simply be infrastructure overhead.
The Case for Provider-Side Parsing
A provider can move some interpretation upstream.
Instead of sending the application a general-purpose event, it can deliver a normalised object containing the fields the target workload is likely to use.
Advantages can include less client CPU, fewer application dependencies, faster integration, simpler strategy code, less program-layout maintenance and potentially lower latency to a usable decision object.
Some specialist infrastructure products compete on this dimension. Subglow describes its pre-parsed Solana data as an extension to Yellowstone-compatible streams for selected trading protocols.
Other providers may offer enhanced APIs, SDKs or parsed data products through different interfaces.
The Trade-Off: Abstraction
Pre-parsed data is an abstraction.
That means the application depends on the provider’s schema, the provider’s interpretation, the set of supported protocols and the speed at which updates are made when a program changes.
If a protocol introduces a new instruction and the provider parser has not yet been updated, a raw-data consumer may be able to adapt faster.
The team must therefore decide whether convenience outweighs abstraction risk.
A Hybrid Architecture
Many applications do not need to choose one approach exclusively.
A strong design can use parsed data for the latency-sensitive hot path while retaining access to raw data for verification, uncommon instructions or later analysis.
For example:
parsed event → strategy
Solana stream →
raw event → archive / verifier
This preserves fast application logic without losing the ability to inspect the underlying transaction.
Another option is to consume raw data but run a dedicated internal parsing service so individual trading strategies do not each implement decoding independently.
Benchmark the Usable Event, Not the Packet
If performance is the reason for choosing parsed data, benchmark it correctly.
Do not simply compare the arrival time of a packet from one provider against the arrival time from another.
Instead, compare the time until the application has a normalised object it can actually use.
That includes parsing.
A raw stream arriving earlier can still produce a later strategy decision if the client spends significant time decoding it.
Conversely, a highly optimised local parser may outperform a generalised provider-side parser.
Only measurement can answer the question.
Schema Design Matters
If a team uses parsed data, the schema should be evaluated just like any other API.
Consider whether numeric units are explicit, public keys are represented consistently and optional fields are handled appropriately. It is also important to consider whether schema versions are documented, unknown instruction types can pass through, the original transaction signature is preserved and the raw message can be retrieved when necessary.
A convenient parser that hides critical information can become a liability.
Maintenance Is Part of the Cost
Teams often compare only infrastructure bills.
But parsing also has a maintenance cost. Program upgrades need to be monitored, account layouts updated, instruction variants added, edge cases fixed, tests created and language dependencies maintained.
For a company with an infrastructure team, this may be routine.
For a small trading team, buying a maintained parsed feed may be economically rational even if the monthly API bill is higher.
Security and Correctness
Never treat parsed data as automatically correct.
For execution-critical systems, important numeric fields should be validated and transaction signatures retained. Sanity checks should be used, parsers tested against known transactions and fallbacks maintained for unexpected schema changes.
The closer a field is to a trading decision, the more valuable independent validation becomes.
Conclusion
Raw and pre-parsed Solana data are not competing philosophies. They are different locations for the same work.
Raw streams maximise control and flexibility.
Provider-side parsing can reduce integration time and client work for defined use cases.
The best architecture depends on how much of parsing is strategic, how much is commodity plumbing, and how many milliseconds it consumes in the real application.
Measure those factors before deciding where decoding belongs.