Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Specification for storing geospatial vector data (point, line, polygon) in Parquet
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
ETL framework for .NET (Parser / Writer for CSV, Flat, Xml, JSON, Key-Value, Parquet, Yaml, Avro formatted files)
EasyDB is a lightweight desktop app built with Tauri + Rust, powered by Apache DataFusion. Query local CSV, TSV, Text, NdJson, Excel, Parquet files and MySQL databases directly with SQL — no external database required. Handles datasets from hundreds of MB to several GB with ease. 让所有数据说同一种“语言”
High-performance analytical database. 19.9M records/sec ingestion, 8.4M+ rows/sec queries. Ingestion, compaction, SQL, retention, continuous queries — one binary. Open Parquet on your storage. S3/Azure native. Air-gap ready. No vendor lock-in. AGPL-3.0.
An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.
sql driver for CSV, TSV, LTSV, JSON, Parquet, Excel with gzip, bzip2, xz, zstd support.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Specification for storing geospatial vector data (point, line, polygon) in Parquet
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
ETL framework for .NET (Parser / Writer for CSV, Flat, Xml, JSON, Key-Value, Parquet, Yaml, Avro formatted files)
EasyDB is a lightweight desktop app built with Tauri + Rust, powered by Apache DataFusion. Query local CSV, TSV, Text, NdJson, Excel, Parquet files and MySQL databases directly with SQL — no external database required. Handles datasets from hundreds of MB to several GB with ease. 让所有数据说同一种“语言”
High-performance analytical database. 19.9M records/sec ingestion, 8.4M+ rows/sec queries. Ingestion, compaction, SQL, retention, continuous queries — one binary. Open Parquet on your storage. S3/Azure native. Air-gap ready. No vendor lock-in. AGPL-3.0.
An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.
sql driver for CSV, TSV, LTSV, JSON, Parquet, Excel with gzip, bzip2, xz, zstd support.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Specification for storing geospatial vector data (point, line, polygon) in Parquet
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
ETL framework for .NET (Parser / Writer for CSV, Flat, Xml, JSON, Key-Value, Parquet, Yaml, Avro formatted files)
EasyDB is a lightweight desktop app built with Tauri + Rust, powered by Apache DataFusion. Query local CSV, TSV, Text, NdJson, Excel, Parquet files and MySQL databases directly with SQL — no external database required. Handles datasets from hundreds of MB to several GB with ease. 让所有数据说同一种“语言”
High-performance analytical database. 19.9M records/sec ingestion, 8.4M+ rows/sec queries. Ingestion, compaction, SQL, retention, continuous queries — one binary. Open Parquet on your storage. S3/Azure native. Air-gap ready. No vendor lock-in. AGPL-3.0.
An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.
sql driver for CSV, TSV, LTSV, JSON, Parquet, Excel with gzip, bzip2, xz, zstd support.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Specification for storing geospatial vector data (point, line, polygon) in Parquet
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
ETL framework for .NET (Parser / Writer for CSV, Flat, Xml, JSON, Key-Value, Parquet, Yaml, Avro formatted files)
EasyDB is a lightweight desktop app built with Tauri + Rust, powered by Apache DataFusion. Query local CSV, TSV, Text, NdJson, Excel, Parquet files and MySQL databases directly with SQL — no external database required. Handles datasets from hundreds of MB to several GB with ease. 让所有数据说同一种“语言”
High-performance analytical database. 19.9M records/sec ingestion, 8.4M+ rows/sec queries. Ingestion, compaction, SQL, retention, continuous queries — one binary. Open Parquet on your storage. S3/Azure native. Air-gap ready. No vendor lock-in. AGPL-3.0.
An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.
sql driver for CSV, TSV, LTSV, JSON, Parquet, Excel with gzip, bzip2, xz, zstd support.