Json-buffet Alternatives
Similar projects and alternatives to json-buffet
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InfluxDB
Purpose built for real-time analytics at any scale. InfluxDB Platform is powered by columnar analytics, optimized for cost-efficient storage, and built with open data standards.
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simdjson
Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
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octosql
OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
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msgspec
A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
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SaaSHub
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ustore
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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japronto
Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.
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ucall
Web Serving and Remote Procedure Calls at 50x lower latency and 70x higher bandwidth than FastAPI, implementing JSON-RPC & REST over io_uring ☎️
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semi_index
Implementation of the JSON semi-index described in the paper "Semi-Indexing Semi-Structured Data in Tiny Space"
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typedload
Discontinued Python library to load dynamically typed data into statically typed data structures
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SaaSHub
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json-buffet discussion
json-buffet reviews and mentions
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Analyzing multi-gigabyte JSON files locally
And here's the code: https://github.com/multiversal-ventures/json-buffet
The API isn't the best. I'd have preferred an iterator based solution as opposed to this callback based one. But we worked with what rapidjson gave us for the proof of concept.
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
Ha! Thanks to you, Today I found out how big those uncompressed JSON files really are (the data wasn't accessible to me, so i shared the tool with my colleague and he was the one who ran the queries on his laptop): https://www.dolthub.com/blog/2022-09-02-a-trillion-prices/ .
And yep, it was more or less they way you did with ijson. I found ijson just a day after I finished the prototype. Rapidjson would probably be faster. Especially after enabling SIMD. But the indexing was a one time thing.
We have open sourced the codebase. Here's the link: https://github.com/multiversal-ventures/json-buffet . Since this was a quick and dirty prototype, comments were sparse. I have updated the Readme, and added a sample json-fetcher. Hope this is more useful for you.
Another unwritten TODO was to nudge the data providers towards a more streaming friendly compression formats - and then just create an index to fetch the data directly from their compressed archives. That would have saved everyone a LOT of $$$.
Stats
multiversal-ventures/json-buffet is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of json-buffet is C++.
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