ucall
java-json-benchmark
| ucall | java-json-benchmark | |
|---|---|---|
| 13 | 5 | |
| 990 | 928 | |
| 1.6% | - | |
| 6.4 | 6.0 | |
| 19 days ago | 15 days ago | |
| C | Java | |
| Apache License 2.0 | MIT License |
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ucall
- Show HN: U)Search Images demo in 200 lines of Python
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Faster JSON-RPC on Linux kernel 5.19+ with io_uring and simdjson
Type checking was included, and union support is trivial to add. We have just added a feature request and will release it in a few days.
- FLiP Stack Weekly for 13 March 2023
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
You are right! For the convenience of Python users, we have to introspect the messages and parse JSON into Python objects. Every member of every dictionary being allocated on heap.
To make it as fast as possible we don't use PyBind, NanoBind, SWIG, or any high-level tooling. Our Python bindings are a pure CPython integration. There is just no way to beat that combo, not that I know.
https://github.com/unum-cloud/ujrpc/blob/main/src/python.c
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Lightweight RPC with `simdjson` and `io_uring` on Linux 5.19 and newer
TLDR: UJRPC reaches 230K TCP/IP round-trips per second on 1 socket. Faster than gRPC and much faster than FastAPI.
- Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19+
java-json-benchmark
- Any fresh jvm21 benchmarks ?
- The Newest Java Json Benchmark Results just dropped
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Serverless Speed: Rust vs. Go, Java, and Python in AWS Lambda Functions
https://github.com/fabienrenaud/java-json-benchmark is an older benchmark. Jsoniter / DslJson haven't really had updates in a while.
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Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19+
It depends. Some binary encodings such as flatbuffer are actually slower than some JSON libraries. There's a wide range of performance even in the JSON libraries themselves. Generally the faster JSON libraries are the ones that work on a predefined schema and so are able to generate code specifically for that JSON.
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Is there a reason to not use Spring Data JPA and Jackson in big projects?
The org.json library is a great little library,. I use it all the time. Just make sure you don't use it for anything that you want to be high performance... We noticed a bottle neck in our application around the reading and writing of json. I did a little reading and found that it was one of the slower libraries out there. https://github.com/fabienrenaud/java-json-benchmark
What are some alternatives?
frontman - Frontman is an open-source API gateway written in Go that allows you to manage your microservices and expose them as a single API endpoint. It acts as a reverse proxy and handles requests from clients, routing them to the appropriate backend service.
fastjson2 - 🚄 FASTJSON2 is a Java JSON library with excellent performance.
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
MyBatis - MyBatis SQL mapper framework for Java
japronto - Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.
fastjson - FASTJSON 2.0.x has been released, faster and more secure, recommend you upgrade.
simdjson - Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
jackson-databind - General data-binding package for Jackson (2.x): works on streaming API (core) implementation(s)
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
json_benchmarks - Java Json library benchmarks
Muonbase - Document Database
jvm-serializers - Benchmark comparing serialization libraries on the JVM