Comparison
datastore.sh vs SonarX
Warehouse data delivery · reviewed September 2026
Short answer
SonarX makes blockchain data available inside cloud data warehouses and marketplaces, so analysts query it in SQL next to their existing tables. datastore.sh delivers Solana and Hyperliquid history as Parquet files you own outright. A share ends when the subscription ends; delivered files do not.
What SonarX is
SonarX describes a warehouse-first delivery model: blockchain data reachable through cloud data platforms and marketplace listings, queried with the SQL tools a team already runs. For an organization standardized on one warehouse, that removes both integration work and a separate vendor interface.
File delivery separates the data from the query environment. Parquet reads natively in Spark, DuckDB, ClickHouse, Snowflake, BigQuery, pandas, and Polars, so the same archive serves a notebook, a cluster, and a warehouse without being tied to any of them, and without a subscription governing continued access.
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 | SonarX |
|---|---|---|
| What you receive | Partitioned Parquet files with typed schemas, manifests, and checksums | Shared tables or listings inside a cloud warehouse |
| Ownership | Files are yours permanently once delivered | Access persists while the subscription or share is active |
| Portability | Open Parquet, readable by any engine | Tied to the warehouse platform hosting the share |
| Compute cost of a scan | Your choice of engine, including local DuckDB | Warehouse compute on every query |
| Setup | Download or receive a drop into your bucket | Attach a share inside the warehouse |
| Coverage shape | Solana and Hyperliquid, decoded per program | Breadth across supported networks |
| Version control | Immutable versions with manifests and checksums | Vendor-managed table updates |
| Best fit | Owned archives, reproducible pipelines, mixed engines | Teams standardized on one warehouse |
When SonarX is the better choice
- Your analysts work exclusively inside one cloud warehouse and want zero setup.
- Joining blockchain data against internal tables in that warehouse is the main use case.
- A live share that the vendor keeps current matters more than permanent retention.
When datastore.sh is the better choice
- You want the archive to survive the end of any subscription.
- Workloads run across several engines, including local analysis and training clusters.
- Repeated full scans would otherwise accumulate warehouse compute cost.
- You need Solana instruction-level detail rather than warehouse-shaped summary tables.
Using both together
The models are compatible. A warehouse share is a convenient way to explore, and Parquet delivery is a durable way to retain what proved useful. Files can be loaded into the same warehouse, so choosing delivery does not mean leaving the environment your analysts already use.
Frequently asked questions
What is the difference between datastore.sh and SonarX?
SonarX makes blockchain data available inside cloud data warehouses and marketplaces, so analysts query it in SQL next to their existing tables. datastore.sh delivers Solana and Hyperliquid history as Parquet files you own outright. A share ends when the subscription ends; delivered files do not.
Can I load datastore.sh files into Snowflake or BigQuery?
Yes. Parquet is a native format for Snowflake, BigQuery, Databricks, Spark, ClickHouse, DuckDB, pandas, and Polars. Files can be loaded from your own bucket with no proprietary connector, which means the same delivery serves warehouse analysts and local research without a second purchase.
What happens to warehouse shares when a contract ends?
Access to a share is revoked when the agreement ends, so anything you need afterward has to be materialized into your own tables while the share is live. Delivered files avoid that step: the archive is already in your storage, with manifests and checksums, and stays readable regardless of the commercial relationship.
Start with the data
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