bytewax
quix-streams
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bytewax | quix-streams | |
---|---|---|
18 | 25 | |
1,144 | 570 | |
8.2% | 35.3% | |
9.8 | 9.0 | |
6 days ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
bytewax
- Building a streaming SQL engine with Arrow and DataFusion
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Near Real Time Ingestion to DB using Python
You can probably use Python to solve your problem, there are many ways you can speed up your deserialization/flattening. I work on Bytewax (https://github.com/bytewax/bytewax) and I wouldn't mention it if it wasn't a good fit, but I think it's worth looking at here. It is a stream processor that makes it easy to scale, maintain order, track progress, and you just write native Python.
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Stream processing framework for a new project in Python
Disclaimer: I work on Bytewax, but it feels like this could be a good fit and would save you some time looking around. If you need to do stateful operations (reduce, window, etc.) then you can use bytewax - https://github.com/bytewax/bytewax with pub/sub, but you would need to build a custom connector. There are some guides on how to do that - https://www.bytewax.io/blog/custom-input-connector.
- What are your favorite tools or components in the Kafka ecosystem?
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A Python package for streaming synthetic data
This is great, definitely see the utility here. I have had to hack this together so many times while building streaming workflows with github.com/bytewax/bytewax and other tools.
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Snowflake - what are the streaming capabilities it provides?
When low latency matters you should always consider an ETL approach rather than ELT, e.g. collect data in Kafka and process using Kafka Streams/Flink in Java or Quix Streams/Bytewax in Python, then sink it to Snowflake where you can handle non-critical workloads (as is the case for 99% of BI/analytics). This way you can choose the right path for your data depending on how quickly it needs to be served.
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Sunday Daily Thread: What's everyone working on this week?
Working on how to use https://github.com/bytewax/bytewax to create embeddings in real-time for ML use cases. I want to make a small library for embedding pipelines, but still learning about vector dbs and the tradeoffs between the different solutions.
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Arroyo: A distributed stream processing engine written in Rust
Project looks cool! Glad you open sourced it. It could use some comments in the code base to help contributors ;). I also like the datafusion usage, that is awesome. BTW I work on github.com/bytewax/bytewax, which is based on https://github.com/TimelyDataflow/timely-dataflow another Rust dataflow computation engine.
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Launch HN: BuildFlow (YC W23) – The FastAPI of data pipelines
Cool, nice idea. Can you sub in different backend like bytewax (https://github.com/bytewax/bytewax) for stateful processing?
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Kafka Stream Processing in Java or Scala
If you want to keep in your Python/SQL area of expertise and by all means I don't mean to promote not learning a new language, but just as an FYI. There are some non-Java/Scala tools between streaming databases like risingwave and materialize, streaming platforms like fluvio and redpanda, and stream processors like bytewax and faust.
quix-streams
- Show HN: Streaming DataFrames–a Pandas-like syntax for real-time data
- FLaNK AI-April 22, 2024
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Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
Airflow for Streaming
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Apache Pulsar VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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redpanda VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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ApacheKafka VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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flink-statefun VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Apache Spark VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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beam VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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debezium VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
Debezium is a change data capture framework for streaming. Connect it to your databases to detect changes and produce those change events to Kafka. Quix Streams is a Python stream processing library for ML and AI applications. It builds on the Confluent Python library to add a state store with RocksDB and adds a Streaming DataFrames API with declarative operations like Windows. It is designed for analytics and data engineering workloads. Use it together with Debezium to process your CDC data in real-time.
What are some alternatives?
timely-dataflow - A modular implementation of timely dataflow in Rust
confluent-kafka-python - Confluent's Kafka Python Client
arroyo - Distributed stream processing engine in Rust
aiokafka - asyncio client for kafka
2022-bytewax-redpanda-air-quality-monitoring
quix-samples - Library samples repository of Quix. Explore and Deploy them easily on https://portal.platform.quix.ai
django-unicorn - The magical reactive component framework for Django ✨
qr-code - A no-framework, no-dependencies, customizable, animate-able, SVG-based <qr-code> HTML element.
Django - The Web framework for perfectionists with deadlines.
csv-import - The open-source CSV importer, maintained by @tableflowhq
Pyramid - Pyramid - A Python web framework
ml-runtimes