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Awesome GitHub RepositoriesExternal Schema Resolvers

Automatic detection of column names and types from external data structures for integration.

Distinct from Data Type Schemas: Focuses on auto-resolving schemas from external sources rather than general type verification.

Explore 2 awesome GitHub repositories matching data & databases · External Schema Resolvers. Refine with filters or upvote what's useful.

Awesome External Schema Resolvers GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • hazelcast/hazelcastAvatar hazelcast

    hazelcast/hazelcast

    6,570Vezi pe GitHub↗

    Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

    Inspects external data structures to automatically detect column names and types.

    Javabig-datacachingdata-in-motion
    Vezi pe GitHub↗6,570
  • kotlin/dataframeAvatar Kotlin

    Kotlin/dataframe

    1,049Vezi pe GitHub↗

    This library is a data processing framework for the JVM that provides a type-safe environment for manipulating structured tabular data. It functions as a comprehensive toolset for performing complex data transformations, aggregations, and statistical analysis, while leveraging compile-time schema validation to ensure structural integrity across data pipelines. The project distinguishes itself through its deep integration with interactive notebook environments and its use of compile-time code generation. By automatically deriving and enforcing schemas from raw inputs, it generates type-safe ac

    Automatically creates type-safe data structures from external definitions to ensure consistency when working with remote data.

    Kotlindata-analysisdata-sciencedataframe
    Vezi pe GitHub↗1,049
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