Most beginner tutorials treat “get crypto data” as one problem with one solution: call an API, done. It’s actually two separate problems wearing the same trench coat. Market data — prices, volume, market cap — comes from centralized APIs like CoinGecko or CoinMarketCap. On-chain data — actual transactions, wallet balances, smart contract state — comes from a blockchain node, and nothing else gives you that directly. Neither one, on its own, gets you anywhere near a forward-looking solana price prediction 2027; that’s a modeling layer built on top of both, not something a raw data pipeline produces by itself.
Conflating those two data planes is where most first attempts at a crypto tool go sideways. A price widget needs the first one. A wallet tracker or a DeFi dashboard needs the second. A lot of tutorials quietly assume you only ever need one, and the code stops working the moment a project needs both.
The two data planes, side by side
|
|
Market data API |
Blockchain node / RPC |
|
What it gives you |
Price, volume, market cap |
Raw transactions, balances, contract state |
|
Source |
Centralized (CoinGecko, CoinMarketCap) |
The chain itself (Ethereum, Solana, etc.) |
|
Access method |
REST calls, API key |
JSON-RPC calls to a node endpoint |
|
Typical library |
Direct HTTP requests |
ethers.js, viem, web3.py, Solana web3.js |
|
Where you’d run it |
Anywhere, no infrastructure |
Self-hosted node, or a hosted RPC provider |
What running your own node actually costs
This is the number most beginner guides skip entirely. As of mid-2026, a synced Ethereum full node needs roughly 1.2 to 1.4 terabytes of NVMe storage, not a spinning hard drive, since the random-write pattern during sync will stall a slower disk for days. With decent hardware, that sync completes in one to two days; on underpowered storage, it can simply never finish. An archive node, which keeps every historical state instead of just recent blocks, runs anywhere from 2 to over 10 terabytes depending on the client, and most beginner tools don’t actually need one. For a first project, a hosted RPC endpoint from a provider is almost always the right call. Running your own node earns its cost only once query volume or privacy requirements justify the hardware and maintenance.
Picking a library without over-engineering the first version
On the Ethereum side, ethers.js has been the default for years and remains the safest choice if you’re following existing tutorials, but it ships around 200kB. viem, the newer TypeScript-first alternative that wagmi is built on, does comparable work at roughly 35kB and with stronger type safety, which matters more than it sounds like once a contract ABI is involved. For Python-based tools, web3.py covers the same ground with one quirk worth knowing early: it rejects lowercase addresses outright and expects them checksummed, which trips up a surprising number of first scripts. On Solana, the equivalent entry point is Solana’s own web3.js library talking to an RPC endpoint rather than a self-hosted validator, since running a Solana validator is a heavier commitment than most data-tool projects need.
Where a simple pipeline breaks
A pruned full node keeps recent state and discards the rest, which is fine for checking a current balance and useless for reconstructing history. Ask it for a wallet’s activity from two years ago and it has nothing to give you; that’s what archive nodes exist for, at several times the storage cost. This is also exactly where a DIY tool hits its ceiling and a specialized historical data provider becomes the more sensible layer instead of trying to run an archive node just to answer one backward-looking question.
Who this setup is actually for
A market-data-only tool, prices and charts, is a weekend project: pick an API, cache responses, done. Add on-chain reads and the honest scope grows to a real backend, even using a hosted RPC provider instead of your own node. Self-hosting a node only makes sense once you’re making enough calls that provider rate limits become the bottleneck, or once data privacy rules out sending every query to a third party — for a first build, or for anything under a few thousand requests a day, that threshold almost never gets crossed, and a hosted endpoint will outperform the self-hosted version on uptime alone.