
Streaming JSON in Rust
Terabytes of JSON, kilobytes of memory
What it does
Streaming JSON is a set of Rust libraries for parsing and transforming JSON using a sliding window approach, without loading the full document into memory. It includes: - "RJiter": a streaming JSON parser - "scan_json": trigger actions during parsing by matching keys and nested structures - "id_transform": copy input to output, a base for JSON rewriting - "ddb_convert": convert JSON to/from DynamoDB format, 12× faster than Python and 2× faster than a baseline Rust implementation
Does a similar job
all alternatives →- PJPython JSON library in Rust, faster than ujson2018 · github.com · ▲40
- AFApache Fory Rust – 10-20x faster serialization than JSON/ProtobufOct 2025 · fory.apache.org · ▲67
Serialization framework with some interesting numbers: 10-20x faster on nested objects than json/protobuf. Technical approach: compile-time codegen (no reflection), compact binary protocol with meta-packing, little-endian layout optimized for modern CPUs. Unique features that other fast serializers don't have: - Cross-language without IDL files (Rust ↔ Python/Java/Go) - Trait object serialization (Box) - Automatic circular reference handling - Schema evolution without coordination Happy to discuss design trade-offs. Benchmarks:…
- SRSwimOS Rust – A framework for real-time streaming data applications2024 · github.com · ▲71
- DEDenormalized – Embeddable Stream Processing in Rust and DataFusion2024 · github.com · ▲125
tl;dr we built an embeddable stream processing engine in Rust using apache DataFusion, check us out at https://github.com/probably-nothing-labs/denormalized Hey HN, We’d like to showcase a very early version of our embeddable stream processing engine called Denormalized. The rise of DuckDB has abundantly made it clear that even for many workloads of Terabyte scale, a single node system outshines the distributed query engines of previous generation such as Spark, Snowflake etc in terms of both performance and cost. Now a lot of workloads DuckDB is used for were normally…
- JTJSON-Threat-Protection Rust High-Performance Crate2024 · github.com · ▲34
- IJIncremental JSON parser for streaming LLM tool calls in RubyOct 2025 · aha.io · ▲13
Built this for streaming AI tool calls. LLMs stream function arguments as JSON character-by-character. Most parsers reparse from scratch each time - O(n²) behavior that causes UI lag. This maintains parsing state, processing only new characters. True O(n) performance that stays imperceptible throughout the entire response. Ruby gem, MIT licensed. Would love feedback.
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