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How does Hydrolix make queries more efficient than other cloud data platforms?

Hydrolix improves query efficiency compared to other cloud data platforms through its unique architecture. Our decoupled and stateless design separates ingest and query resources from storage, allowing us to focus on efficiently handling high-cardinality and high-dimensionality data. Here’s how our architecture achieves query efficiency: Scalable Query Pools: Hydrolix enables you to scale query resources independently,…

Jay Maloney

Published:

Oct 30, 2023

1 minute read

Hydrolix improves query efficiency compared to other cloud data platforms through its unique architecture. Our decoupled and stateless design separates ingest and query resources from storage, allowing us to focus on efficiently handling high-cardinality and high-dimensionality data.

Here’s how our architecture achieves query efficiency:

  • Scalable Query Pools: Hydrolix enables you to scale query resources independently, ensuring consistently low-latency queries as your data workload grows.
  • Partition Metadata: We utilize partition metadata to speed up time-based queries, which is particularly beneficial for time-series data analysis.
  • Full Column Indexing: Hydrolix leverages full-column indexing, which optimizes query performance by swiftly locating the necessary data.
  • Predicate Pushdown: Our platform efficiently filters datasets using predicate pushdown, further enhancing query efficiency.

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Hydrolix improves query efficiency compared to other cloud data platforms through its unique architecture. Our decoupled and stateless design separates ingest and query resources from storage, allowing us to focus on efficiently handling high-cardinality and high-dimensionality data.

Here’s how our architecture achieves query efficiency:

  • Scalable Query Pools: Hydrolix enables you to scale query resources independently, ensuring consistently low-latency queries as your data workload grows.
  • Partition Metadata: We utilize partition metadata to speed up time-based queries, which is particularly beneficial for time-series data analysis.
  • Full Column Indexing: Hydrolix leverages full-column indexing, which optimizes query performance by swiftly locating the necessary data.
  • Predicate Pushdown: Our platform efficiently filters datasets using predicate pushdown, further enhancing query efficiency.