Instant Kubernetes-Native Application Observability
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Updated
May 10, 2023 - C++
Instant Kubernetes-Native Application Observability
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).
Modern columnar data format for ML implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..
Manipulate JSON-like data with NumPy-like idioms.
Infrastructures™ for Machine Learning Training/Inference in Production.
Replacing MongoDB, Neo4J, and Elastic with 1 transactional database. Features: zero-copy semantics, swappable backends, bindings for C, C++, Python, Java, GoLang
A Rust DataFrame implementation, built on Apache Arrow
Geospatial extensions for Polars
A SQLite vtable extension to read Parquet files
Manipulate arrays of complex data structures as easily as Numpy.
Fletcher: A framework to integrate FPGA accelerators with Apache Arrow
Rust-based WebAssembly bindings to read and write Apache Parquet data
Pod5: a high performance file format for nanopore reads.
OSM planet dump high performance data loader. Transform OpenStreetMap World/Region PBF dump into partitioned by H3 regions PostGIS pgsnapshot (lossless) OSM schema representation and/or into ArrowIPC/Parquet dumps
A simple dataframe library for Ruby
In-memory, columnar, arrow-based database.
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