Dune SQL Migration Update

We hit day 30 of our 90 day DuneSQL Migration Plan, here's how it's going so far

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On April 20th, we announced the migration to DuneSQL. We are investing heavily in DuneSQL to make the fastest, most powerful and convenient crypto data querying experience on the planet. With DuneSQL we are releasing powerful features including:

  • The ability to use queries as views
  • Wei-level precision via UINT256 and INT256 datatypes
  • Ability to select performance levels for your query
  • Queries as materialized views
  • Scheduled queries
  • Upload your own data and query it with DuneSQL

We're focusing all our efforts going forward, and will be progressively sunsetting both SparkSQL and V1 (Postgres) to make DuneSQL the only query engine.

In our migration announcement, we highlighted our commitment to a seamless transition process. Our efforts are currently focused on:

  • Supporting migration efforts with powerful features to migrate your queries
  • Continuously improving DuneSQL’s stability and performance
  • Transitioning Spellbook from SparkSQL to DuneSQL

Here are key updates on those areas as we hit the 30 day mark of our 90 day sunsetting plan.

Supporting migration efforts

Harmonizer, the “migrate to DuneSQL” feature, has been improved significantly.

You can now use it to handle more complex translations like translating Spark’s `explode(array_column)`  into Trino’s `cross join from unnest(array_column)`.

Harmonizer can be used to translate your Ethereum V1 and SparkSQL queries. The full set of updates are available here

Give the latest version a try for your Ethereum V1 and SparkSQL queries and continue to send us your feedback!

Continuously improving DuneSQL

Performance has largely been addressed in DuneSQL with the rollout of performance tiers, materialization of nft.trades/dex.trades, and improvements to the overall engine. 

To address the excessive stages and optimizer timeout issues of more advanced queries, we are rolling out materialized views in late June.

Materialized views will allow your team to break down complex queries into multiple materialized views. These create mini-data pipelines that will run more efficiently and allow you to work around stage-related timeout issues from a single large query.

Transitioning to DuneSQL Spellbook 

Finally, we completed testing the DuneSQL Spellbook and are confident that it is the best solution moving forward.

Over the next few weeks we'll be rolling out the DuneSQL spellbook and moving the SparkSQL spellbook into maintenance mode (no new PRs and SparkSQL removed from the dropdown).

For our community of creators this will have no noticeable impact. When querying spells from DuneSQL, you can continue to use Spells like you do today. For contributors to spellbook, we will announce a more detailed timeline shortly.

To reiterate, once Spellbook on DuneSQL has been fully validated, all Spells will be migrated by the Dune Team.

One last note

The high-level timeline for SparkSQL and PostgreSQL along with FAQ are available now in our docs.

Please refer to the docs to keep up to date with the progress:

Thank you for your continued trust and support during this migration, we hope you’re loving the new capabilities DuneSQL has to offer. We appreciate your patience during this transition.

Don’t hesitate to reach out to us via for any questions or concerns.

The data must flow!

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