Comparison
datastore.sh vs Chainbase
Multi-chain data infrastructure · reviewed September 2026
Short answer
Chainbase provides multi-chain data infrastructure, exposing indexed blockchain data through APIs and hosted datasets across many networks. datastore.sh publishes two networks, Solana and Hyperliquid, as partitioned Parquet files delivered to storage you control. The tradeoff is breadth with hosted access against depth with owned files and pinned schemas.
What Chainbase is
Chainbase positions itself as data infrastructure for many chains, with indexed data reachable through APIs and hosted datasets, aimed at developers and at AI and analytics workloads that want one access layer across networks.
datastore.sh takes the opposite shape. Fewer networks, decoded further, published as files rather than as an access layer. There is no runtime dependency on our service once a delivery completes, which is the property that matters for reproducible research and for environments that cannot call outside.
How the two products differ
The comparison is between product models rather than feature lists. Prices, rate limits, and chain counts change without notice, so none are quoted here.
| Dimension | datastore.sh | Chainbase |
|---|---|---|
| What you receive | Partitioned Parquet files with typed schemas, manifests, and checksums | API responses and hosted datasets across many chains |
| Coverage strategy | Two networks, decoded to instruction level | Many networks through one access layer |
| Runtime dependency | None after delivery, since files are local | Availability and limits of the hosted service |
| Format | Open Parquet with documented, typed schemas | Service-defined responses and dataset formats |
| Reproducibility | Immutable versions, verified by checksum | Depends on how the hosted dataset is versioned |
| Cost of repeated full scans | Free after the initial purchase | Metered by the plan in use |
| Offline or restricted environments | Supported, since data moves into your perimeter | Requires access to the service |
| Best fit | Deep archives for research, backtests, and training | Multi-chain application and analytics access |
When Chainbase is the better choice
- You build across many chains and want one integration rather than several archives.
- Your workload is application-shaped: queries by address, token, or contract, served live.
- Breadth of network coverage matters more than instruction-level depth on any one chain.
When datastore.sh is the better choice
- Solana or Hyperliquid is the scope, and you need decoded instructions rather than summaries.
- The dataset must be reproducible byte for byte, months after it was delivered.
- Training or backtesting will scan the full range repeatedly.
- The environment that consumes the data cannot depend on an external service.
Using both together
A multi-chain access layer answers questions that span networks. A per-program archive answers questions that go deep on one. Teams that need both usually integrate an API for breadth and buy files for the networks their research actually depends on.
Frequently asked questions
What is the difference between datastore.sh and Chainbase?
Chainbase provides multi-chain data infrastructure, exposing indexed blockchain data through APIs and hosted datasets across many networks. datastore.sh publishes two networks, Solana and Hyperliquid, as partitioned Parquet files delivered to storage you control. The tradeoff is breadth with hosted access against depth with owned files and pinned schemas.
Which is better for AI training data?
File delivery is usually the better fit. Training needs a fixed corpus that does not change between runs, sits inside the training environment, and can be scanned repeatedly at no marginal cost. Parquet files with immutable schema versions and checksums meet those requirements. A hosted access layer is better when the model needs live lookups at inference time.
Can I get multi-chain coverage from datastore.sh?
Not today. Coverage is Solana and Hyperliquid, and the catalog documents every dataset and table on those networks. If a workload requires networks outside that scope, a multi-chain provider is the right tool, and the two approaches combine without conflict.
Start with the data
Skip the indexing project. Run the query.
Browse documented datasets or send the exact protocol, tables, and historical coverage your team needs.