Apache Arrow Collection

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⚙️Steel

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“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..”

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🔥Fire

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“Instant Kubernetes-Native Application Observability”

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🔮Psychic

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“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).”

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⚙️Steel

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“Apache Kafka® compatible broker with S3, PostgreSQL, SQLite, Apache Iceberg and Delta Lake”

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🌊Water

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“❄️ Coolest database around 🧊 Embeddable column database written in Go.”

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🔮Psychic

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“Manipulate JSON-like data with NumPy-like idioms.”

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🔮Psychic

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“Fast, interactive geospatial data visualization in Jupyter.”

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🔮Psychic

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“Geospatial extensions for Polars”

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💎Aqua

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“Loaders for big data visualization. Website:”

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⚙️Steel

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“Intuitive Data Workflows”

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⚙️Steel

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“Rust-based WebAssembly bindings to read and write Apache Parquet data”

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🔥Fire

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“Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️”

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📦Normal

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“Specification for storing geospatial data in Apache Arrow”

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📦Normal

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“Infrastructures™ for Machine Learning Training/Inference in Production.”

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⚙️Steel

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“GeoArrow in Rust, Python, and JavaScript (WebAssembly) with vectorized geometry operations”

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📦Normal

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“Official Go implementation of Apache Arrow”

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🔥Fire

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“🚀 GizmoSQL — High-Performance Database Server”

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⚙️Steel

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“Lakehouse native graph engine with git-style workflows”