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102 Repos

Awesome GitHub RepositoriesStructured Data Schemas

Tools for defining and managing complex data types and nested structures.

Distinguishing note: Focuses on schema integrity in ETL workflows.

Explore 102 awesome GitHub repositories matching data & databases · Structured Data Schemas. Refine with filters or upvote what's useful.

Awesome Structured Data Schemas GitHub Repositories

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  • pola-rs/polarsAvatar von pola-rs

    pola-rs/polars

    38,855Auf GitHub ansehen↗

    Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e

    Supports complex schemas, nested structures, and categorical types to ensure data integrity during ETL workflows.

    Rustarrowdataframedataframe-library
    Auf GitHub ansehen↗38,855
  • pubkey/rxdbAvatar von pubkey

    pubkey/rxdb

    23,048Auf GitHub ansehen↗

    This project is a reactive, offline-first NoSQL database engine designed for JavaScript applications. It provides a robust framework for managing application state by synchronizing data across browsers, mobile devices, and server-side runtimes. By treating local storage as the primary source of truth, it enables applications to remain functional without network connectivity, automatically reconciling changes with remote backends once a connection is restored. The database distinguishes itself through a modular architecture that supports cross-environment synchronization and high-performance d

    Enforces data consistency and validation using schemas to organize information within the database in a clear and predictable manner.

    TypeScriptangularbrowser-databasecouchdb
    Auf GitHub ansehen↗23,048
  • huggingface/lerobotAvatar von huggingface

    huggingface/lerobot

    21,687Auf GitHub ansehen↗

    This project is a comprehensive research platform designed for the end-to-end lifecycle of robotic learning. It provides a modular framework for training neural network policies—specifically through imitation and reinforcement learning—and deploying them onto physical robotic hardware. By offering a unified interface for hardware abstraction, the platform decouples high-level control logic from the specific sensors and actuators of diverse robotic systems. The framework distinguishes itself through a standardized approach to data and policy management. It utilizes a consistent schema for reco

    Structures interaction data into synchronized video and state files for cross-environment compatibility.

    Python
    Auf GitHub ansehen↗21,687
  • postgres/postgresAvatar von postgres

    postgres/postgres

    20,076Auf GitHub ansehen↗

    PostgreSQL is an object-relational database management system designed for the persistent storage and retrieval of structured information. It functions as an ACID-compliant database server, utilizing standard query language protocols to maintain data consistency and reliability across large-scale application datasets. The system distinguishes itself through an extensible architecture that allows for the definition of custom data types, operators, and indexing methods. It employs multi-version concurrency control to enable simultaneous read and write operations without blocking, supported by a

    Stores records in defined schemas using specific data types to ensure organized and retrievable information.

    C
    Auf GitHub ansehen↗20,076
  • subquery/subqlAvatar von subquery

    subquery/subql

    18,791Auf GitHub ansehen↗

    Subql is a blockchain data indexing framework and TypeScript-based indexer used to extract raw blockchain events and transactions and transform them into structured, queryable data entities. It functions as a data API and a tool for building decentralized application backends, providing a query interface for type-safe access to indexed blockchain data. The project includes an AI-powered query engine that utilizes large language models to translate natural language questions into structured GraphQL queries. This system can orchestrate multi-step queries by breaking down complex requests into s

    Allows the specification of structures and relationships for indexed information to organize the final output.

    TypeScript
    Auf GitHub ansehen↗18,791
  • quickwit-oss/tantivyAvatar von quickwit-oss

    quickwit-oss/tantivy

    15,442Auf GitHub ansehen↗

    Tantivy is a library for building full-text search engines and indexing frameworks. It provides the core components necessary to organize large collections of text data into searchable structures, enabling the execution of complex queries and the retrieval of information across structured document sets. The engine utilizes an inverted index architecture to map terms to document identifiers, supported by a segment-based storage model that balances search performance with write throughput. It incorporates specialized data structures, including finite state transducers for term dictionaries and

    Organizes complex datasets into searchable schemas to enable efficient retrieval and analysis across massive document stores.

    Rustrustsearch-engine
    Auf GitHub ansehen↗15,442
  • adityatelange/hugo-papermodAvatar von adityatelange

    adityatelange/hugo-PaperMod

    13,694Auf GitHub ansehen↗

    This is a responsive website theme for Hugo, providing a minimalist static site template and markdown blog layout. It is designed to prioritize content readability and search engine optimization through a clean, mobile-friendly interface. The theme distinguishes itself with built-in support for light and dark mode switching and a client-side search integration that allows users to query site content without a backend server. It also includes a comprehensive suite of social integration tools for managing OpenGraph and Twitter Card metadata. The project covers broad capability areas including

    Implements structured data and schema publisher types to improve how search engines categorize the site.

    HTMLblogblog-themeclean
    Auf GitHub ansehen↗13,694
  • jackc/pgxAvatar von jackc

    jackc/pgx

    13,428Auf GitHub ansehen↗

    This project is a database driver and interface for the Go programming language, specifically designed for PostgreSQL. It provides a low-level library for executing SQL queries, managing transactions, and handling data persistence within Go applications. The driver distinguishes itself by implementing the native PostgreSQL binary wire protocol, which minimizes communication overhead and maximizes data transfer efficiency. It includes advanced connection pooling to maintain persistent database sessions and supports prepared statement caching to accelerate the execution of frequently repeated o

    Structures API responses based on predefined field definitions to ensure consistent access to documentation and version history.

    Go
    Auf GitHub ansehen↗13,428
  • harelba/qAvatar von harelba

    harelba/q

    10,353Auf GitHub ansehen↗

    q is a command-line utility for the processing, filtering, and aggregation of tabular text and database files using standard SQL syntax. It functions as a query engine that treats CSV and TSV files, as well as standard input, as relational database tables. The tool distinguishes itself by providing a persistent cache layer that stores processed tabular data in a binary format to accelerate repeated queries on large datasets. It also maps individual filenames or stream identifiers to relational table names, enabling SQL joins across disparate text files. The project covers a broad range of da

    Analyzes input files to determine column names from headers and infer data types for every field.

    Pythonclicommand-linecommand-line-tool
    Auf GitHub ansehen↗10,353
  • open-mmlab/mmsegmentationAvatar von open-mmlab

    open-mmlab/mmsegmentation

    9,860Auf GitHub ansehen↗

    MMSegmentation is an open-source semantic segmentation toolbox built on PyTorch that provides a modular, configurable framework for building, training, evaluating, and deploying segmentation models. At its core, it offers a config-driven pipeline that assembles training, evaluation, and inference workflows by parsing hierarchical configuration files, with a modular component registry that enables plug-and-play composition of neural network modules, optimizers, datasets, and metrics. The framework supports the full model lifecycle through a unified runner interface that controls training, testi

    Transforms raw annotations into standardized label maps through a configurable sequence of data transforms and folder structure conventions.

    Pythondeeplabv3image-segmentationmedical-image-segmentation
    Auf GitHub ansehen↗9,860
  • doctrine/dbalAvatar von doctrine

    doctrine/dbal

    9,699Auf GitHub ansehen↗

    This project is a SQL database abstraction layer that provides a consistent object-oriented interface for interacting with multiple relational database systems. It includes a driver wrapper to standardize connections and result sets, a fluent query builder for constructing portable SQL statements, and a type mapper for converting database-specific data types into native application types and vice versa. The library enables programmatic schema management through a schema manager that can introspect database metadata, model structures as objects, and generate the SQL required to migrate between

    Translates application objects into the specific string formats required by the underlying database platform.

    PHPdatabaseibm-db2mariadb
    Auf GitHub ansehen↗9,699
  • iib0011/omni-toolsAvatar von iib0011

    iib0011/omni-tools

    9,710Auf GitHub ansehen↗

    omni-tools is a browser-based utility suite that provides client-side tools for manipulating PDFs, media files, and data formats. It functions as a collection of web-based processors and calculation engines that execute directly within the browser without requiring server-side processing. The suite includes a client-side PDF editor for merging, splitting, and reorganizing document structures, and a web-based media processor for resizing, trimming, and converting image and video files. It also features a data format converter that transforms structured information between JSON, CSV, and XML fo

    Converts structured data between different formats by mapping input fields to specific output templates.

    TypeScriptalternativeconverterdata-manipulation
    Auf GitHub ansehen↗9,710
  • studyzy/imewlconverterAvatar von studyzy

    studyzy/imewlconverter

    9,686Auf GitHub ansehen↗

    imewlconverter is an input method editor wordlist converter and format transformer designed to migrate user dictionaries and phrase lists between different software environments. It functions as a cross-platform dictionary migrator, translating proprietary binary and text wordlists for use across Windows, macOS, and mobile systems. The tool standardizes diverse lexicon formats, such as WL, FIT, DCTX, LD2, and QPYD, into common structures to ensure cross-platform compatibility. It specifically handles binary wordlist extraction and the transformation of custom phrase lists for systems includin

    Transforms wordlists from various input method formats into the DCTX format required for Microsoft Pinyin.

    C#c-sharpchinese-charactersconverter
    Auf GitHub ansehen↗9,686
  • wireshark/wiresharkAvatar von wireshark

    wireshark/wireshark

    9,477Auf GitHub ansehen↗

    Wireshark is a network protocol analyzer and traffic inspector used for capturing and inspecting network traffic. It functions as a packet capture tool that intercepts live data from network interfaces and a TCP/IP dissector that decodes network protocol layers to translate raw binary packets into human-readable fields. The system provides capabilities for protocol stream reconstruction, grouping related packets into cohesive conversations between endpoints. It also operates as a packet file converter, allowing for the reading, modification, and conversion of network capture files across vari

    Writes packets from one capture file to another to change formats or remove specific packets.

    Cpacket-capturestratosharktshark
    Auf GitHub ansehen↗9,477
  • dotnet/machinelearningAvatar von dotnet

    dotnet/machinelearning

    9,329Auf GitHub ansehen↗

    This is a cross-platform framework for building, training, and deploying custom machine learning models within the .NET ecosystem. It provides a predictive modeling engine for classification, regression, and forecasting tasks, alongside an inference runtime to generate predictions across different hardware architectures. The framework includes a gradient boosting library and supports interoperability with external models via a standardized open format. It features tools for prediction explainability, allowing the analysis of feature importance to debug model behavior and identify bias. The p

    Automatically determines input and output data shapes at runtime to support datasets without predefined structures.

    C#algorithmsdotnetmachine-learning
    Auf GitHub ansehen↗9,329
  • lancedb/lancedbAvatar von lancedb

    lancedb/lancedb

    9,031Auf GitHub ansehen↗

    LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters

    Transforms stored data between different registered formats to optimize data layout for inspection.

    HTMLapproximate-nearest-neighbor-searchimage-searchnearest-neighbor-search
    Auf GitHub ansehen↗9,031
  • adaway/adawayAvatar von AdAway

    AdAway/AdAway

    8,816Auf GitHub ansehen↗

    AdAway is an Android network firewall and DNS traffic filter that functions as a local VPN ad blocker. It intercepts network requests to prevent advertisements and tracking domains from reaching the device by filtering traffic against host lists. The project features a host file manager capable of importing and converting blocklists from external third-party providers. It includes a system for managing both blocked and allowed domains, allowing for the creation of custom rules to permit specific trusted sites or block individual domains. The tool provides granular traffic control through app

    Converts blocked and allowed hostname lists between legacy hosts file formats and structured data representations.

    Cad-blockerandroidblocker
    Auf GitHub ansehen↗8,816
  • howtographql/howtographqlAvatar von howtographql

    howtographql/howtographql

    8,708Auf GitHub ansehen↗

    This project is a comprehensive educational resource and fullstack tutorial for GraphQL development. It provides instructional content and guides focused on designing schemas, implementing servers, and managing the end-to-end workflow of building production-ready applications. The material covers the conceptual differences between graph-based data structures and traditional API architectures. It includes a dedicated security course and guides for client integration, teaching users how to fetch data, manage application state, and apply protection measures to secure API endpoints. The scope of

    Provides detailed guidance on structuring data as a graph of types to facilitate efficient retrieval.

    TypeScriptapollographqlgraphqlprisma
    Auf GitHub ansehen↗8,708
  • vowpalwabbit/vowpal_wabbitAvatar von VowpalWabbit

    VowpalWabbit/vowpal_wabbit

    8,683Auf GitHub ansehen↗

    Vowpal Wabbit is an open-source machine learning system designed for online learning, where models update incrementally from streaming data without requiring full retraining. It provides a reduction-based learning framework that composes complex tasks from simpler algorithms, and includes a feature hashing trick that maps unbounded feature names into a fixed-size vector space to keep memory usage constant regardless of dataset size. The system supports distributed training across a cluster using an allreduce protocol for synchronized updates, and offers an active learning query strategy that s

    Transforms pandas DataFrames into the Vowpal Wabbit text format for use with training and prediction tools.

    C++active-learningc-plus-pluscontextual-bandits
    Auf GitHub ansehen↗8,683
  • hypothesisworks/hypothesisAvatar von HypothesisWorks

    HypothesisWorks/hypothesis

    8,717Auf GitHub ansehen↗

    Hypothesis is a Python property-based testing library and data generation engine. It enables the discovery of edge cases and bugs by generating a wide range of randomized inputs based on defined strategies and shrinking complex failing examples to their smallest possible form. It also functions as a state machine testing framework to verify system behavior across sequences of interdependent operations. The project features a fuzzing integration layer that converts raw byte buffers from coverage-guided fuzzers into structured test cases. It includes a persistence mechanism to store and synchro

    Creates data generation strategies by analyzing definitions like JSON Schema, GraphQL, or model definitions.

    Pythonfuzzingproperty-based-testingpython
    Auf GitHub ansehen↗8,717
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  • Automated Structure NormalizationAutomated process of inferring schemas and data types while flattening nested structures into relational datasets. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas by focusing on the active process of inference and normalization rather than just the definition.
  • COVID-19 Hospital Data Schemas2 Sub-TagsSchema mappings of CDC patient and bed count fields to structured properties for interoperable data exchange. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses specifically on COVID-19 hospital data mapping, not general structured data schemas.
  • Class-to-Table MappingsMappings that define how application classes correspond to database table columns. **Distinct from Struct-to-Table Mappings:** Focuses on Java classes rather than Elixir structs.
  • Composable Codec SchemasDescribing data shapes with composable codecs that enforce structural correctness across system boundaries. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses on composable codec-based schemas rather than general data structure definitions.
  • Data Loading UtilitiesTools for populating schema structures with raw data or fetching associated records to resolve complex object relationships. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses on the runtime population and retrieval of data records rather than the definition of schema integrity.
  • Entity Relationship ModelsDefinitions of data structures and relational mappings between entities. **Distinct from Structured Data Schemas:** Focuses on the conceptual modeling of entities and their relationships rather than just the technical schema integrity of ETL workflows.
  • Field Alias MappingMapping schema field names to custom identifiers while preserving original names as aliases. **Distinct from Named Field Schemas:** Distinct from Named Field Schemas by focusing on the renaming process during code generation.
  • Format Conversions14 Sub-TagsProcesses the transformation of structured data from one format to another via mapping logic. **Distinct from Structured Data Schemas:** Focuses on the active conversion process between formats rather than the static definition of the schema itself
  • Graph-Based Schema Design3 Sub-TagsThe process of structuring data as interconnected types and fields for graph APIs. **Distinct from Structured Data Schemas:** Specifically targets the design of graph-based API schemas rather than ETL or internal database structures.
  • Multimodal Unified SchemasSchemas that provide a consistent structure for both tabular data and unstructured media files. **Distinct from Structured Data Schemas:** Specifically handles the unification of structured tables and unstructured media, unlike general structured data schemas.
  • Named Field Schemas1 Sub-TagSchemas with typed properties, optional fields, and default values to represent structured data. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses on named field definitions with optionality and defaults, not general schema integrity in ETL workflows.
  • Protocol Schema DefinitionsShared semantic structures for network data that enable consistent interpretation across independent applications. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses on protocol-level semantic unification for decentralized networks rather than general ETL schema integrity.
  • Query Input SchemasStandardized structures for defining the format and metadata of queries sent to AI services. **Distinct from Structured Data Schemas:** Focuses on the input structure for AI queries rather than general ETL data integrity
  • Robotic Interaction SchemasStandardized structures for synchronized video and state data in robotic interaction datasets. **Distinct from Structured Data Schemas:** Distinct from general structured schemas: focuses on synchronized multi-modal robotic data.
  • Schema Inference4 Sub-TagsAnalyzing raw files to automatically determine column names and structures. **Distinct from Structured Data Schemas:** Focuses on inferring structure from raw text headers rather than managing complex nested schemas.
  • Schema-Aware RetrievalRetrieval mechanisms that structure responses based on predefined data schemas. **Distinct from Structured Data Schemas:** Distinct from structured data schemas: focuses on the retrieval layer's awareness of schema definitions.
  • Search Engine SchemasDefinitions of structured data and schema types used specifically to enhance search engine indexing and categorization. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas by focusing on search engine visibility (SEO) rather than internal ETL data integrity.
  • Struct-to-Table Mappings5 Sub-TagsDeclarative mappings that define how Elixir structs correspond to database table columns and types. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses on mapping application structs to database tables, not general ETL schema definitions.
  • Time-Series Schema WritesConstructs a table object with tag, timestamp, and field columns, then inserts rows to write structured time-series data. **Distinct from Structured Data Schemas:** Distinct from Structured Data Schemas: focuses on writing data with a defined time-series schema, not general schema definition.