Deephaven's and Materialize's query engines both rely heavily on an incremental-update model to empower use cases. Despite this, some of their design fundamentals are quite distinct from one another. Perhaps this can be explained by disparate sets of use cases driving development.
Materialize | Deephaven | |
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Update Cycle |
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Consistency Model |
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BI Exploration & Dashboarding |
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Source Tables |
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Client Library |
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OLTP / OLAP Affinity |
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Sources |
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The architecture fundamentals inherent in the models framed above have implications for data transport and interoperability with other ecosystem tools and user applications. In a nearby post, we articulate a view that, when it comes to dynamic table data, providing a framework that complements the engine matters a lot.