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7 repositorios

Awesome GitHub RepositoriesTable Format Integrations

Querying capabilities for specific table formats like Hudi by integrating with metastores.

Distinct from Virtual Table Querying: Distinct from Virtual Table Querying: focuses on specific storage format integration rather than general table virtualization.

Explore 7 awesome GitHub repositories matching data & databases · Table Format Integrations. Refine with filters or upvote what's useful.

Awesome Table Format Integrations GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • prestodb/prestoAvatar de prestodb

    prestodb/presto

    16,711Ver en GitHub↗

    Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing

    Integrates with metastores to query data stored in specialized table formats like Hudi.

    Javabig-datadatahadoop
    Ver en GitHub↗16,711
  • automq/automqAvatar de AutoMQ

    AutoMQ/automq

    10,027Ver en GitHub↗

    AutoMQ is a cloud-native streaming platform and Apache Kafka distribution that implements a decoupled compute and storage architecture. It functions as an S3-backed message queue, using object storage as the primary log repository to eliminate dependencies on local disks. The platform utilizes a stateless broker architecture to enable dynamic compute scaling and automated partition balancing. This design allows the system to adjust the number of brokers in seconds and distribute network traffic without requiring manual data migration or partition reassignment. The system provides multi-avail

    Combines real-time eventing with analytical processing by integrating streaming data into standardized table formats.

    Java
    Ver en GitHub↗10,027
  • apache/icebergAvatar de apache

    apache/iceberg

    8,972Ver en GitHub↗

    Iceberg is an open table format and big data table manager designed for huge analytic datasets in cloud storage. It provides a specification for tracking large-scale datasets to maintain transactional consistency and structural integrity. The project utilizes a standardized REST catalog interface to manage table metadata, ensuring interoperability between different compute engines. This allows diverse query engines to connect to a single table interface and maintain consistency across different processing frameworks. Its core capabilities include managing large-scale analytic tables, coordin

    Connects diverse compute frameworks to maintain a consistent table interface regardless of the underlying processing engine.

    Java
    Ver en GitHub↗8,972
  • delta-io/deltaAvatar de delta-io

    delta-io/delta

    8,596Ver en GitHub↗

    Delta is a lakehouse table format that brings ACID transactions and data warehouse consistency to large scale data lakes on cloud object storage. It serves as an ACID transaction manager, coordinating atomic commits and serializable isolation for concurrent reads and writes across distributed compute engines. The project provides a multi-engine interoperability layer that uses format translation to allow diverse SQL engines and processing frameworks to read and write the same tables. It functions as a data versioning system, utilizing a transaction log to enable time travel, historical snapsh

    Unifies real-time event streams with structured table formats to read continuous sequences of updates.

    Scalaacidanalyticsbig-data
    Ver en GitHub↗8,596
  • misp/mispAvatar de MISP

    MISP/MISP

    6,360Ver en GitHub↗

    MISP is an open-source threat intelligence sharing platform designed for collecting, storing, and distributing structured threat indicators and intelligence. At its core, it provides a distributed synchronization protocol for transferring events between instances, an attribute-based correlation engine that links matching indicators across events, and a REST API with an OpenAPI specification for programmatic access to threat data. The platform uses formal data formats for JSON, taxonomy, galaxy, and object templates to enable compatibility across tools and communities. The platform distinguish

    Ships formal specifications for JSON, taxonomy, galaxy, and object template formats to enable tool compatibility.

    PHP
    Ver en GitHub↗6,360
  • apache/hudiAvatar de apache

    apache/hudi

    6,097Ver en GitHub↗

    Apache Hudi is an open-source table format that brings ACID transactions, incremental processing, and multi-modal indexing to data lakes. It provides atomic commits with snapshot isolation, rollback, and optimistic concurrency control for reliable data lake operations, while supporting upserts, record-level updates, and deletions in large analytical datasets. The project distinguishes itself through a timeline-based architecture that coordinates all write operations, enabling features like time-travel querying, incremental change streaming, and multi-modal query views that include snapshot, i

    Reads data from Hudi tables using standard Spark SQL or DataFrame APIs for analytical processing.

    Javaapacheflinkapachehudiapachespark
    Ver en GitHub↗6,097
  • kuzudb/kuzuAvatar de kuzudb

    kuzudb/kuzu

    3,965Ver en GitHub↗

    Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data management. It operates as a library within the host application process, utilizing a columnar-based storage architecture and just-in-time query compilation to execute complex graph traversals and pattern matching efficiently. By mapping database files directly into system memory, it ensures data durability and high-speed access while maintaining ACID-compliant transactional integrity. The engine distinguishes itself by integrating vector similarity search and full-text search di

    Queries data directly from table formats like Iceberg and Delta Lake without permanent import.

    C++cypherdatabaseembeddable
    Ver en GitHub↗3,965
  1. Home
  2. Data & Databases
  3. Virtual Table Querying
  4. Table Format Integrations

Explorar subetiquetas

  • Multi-Engine InterfacesInterfaces that allow diverse compute frameworks to maintain a consistent view of the same table format. **Distinct from Table Format Integrations:** Distinct from Table Format Integrations: focuses on the ability to connect multiple different query engines to a single consistent interface.
  • Stream-Table UnificationIntegration of real-time event streams with structured table formats for unified analysis. **Distinct from Table Format Integrations:** Focuses on the unification of streaming and batch/table formats rather than simple integration of one format.
  • Threat Intelligence Format IntegrationsIntegration points for consuming and producing threat intelligence data in standardized formats like JSON, taxonomy, galaxy, and object templates. **Distinct from Table Format Integrations:** Distinct from Table Format Integrations: focuses on threat intelligence data formats, not database table formats.