bytewax
debezium
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bytewax | debezium | |
---|---|---|
18 | 80 | |
1,144 | 9,884 | |
8.2% | 2.0% | |
9.8 | 9.9 | |
6 days ago | about 20 hours ago | |
Python | Java | |
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.
debezium
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
They manage data in the application layer and your original data stays where it is. This way data consistency is no longer an issue as it was with streaming databases. You can use Change Data Capture (CDC) services like Debezium by directly connecting to your primary database, doing computational work, and saving the result back or sending real-time data to output streams.
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Generating Avro Schemas from Go types
Both of these articles mention a key player, Debezium. In fact, Debezium has had a place in the modern infrastructure. Let's use a diagram to understand why.
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debezium VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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How the heck do I validate records with this kind of data??
This might be overkill, but you could use an extra tool like https://debezium.io to capture logs about all creates, updates, and deletes in your table
- All the ways to capture changes in Postgres
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Managed Relational Databases with AWS RDS and Aurora
If you're considering a relational database for an event-driven architecture, check out Debezium. It lets you stream changes to relational databases, and subscribe to change events.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
Debezium
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Postgresql to hadoop in real time
https://debezium.io/ comes to mind as an open source product, but there are a gazillion of these tools out there.
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ClickHouse Advanced Tutorial: Apply CDC from MySQL to ClickHouse
Contrary to what it sounds, it’s quite straightforward. The database changes are captured via Debezium and published as events on Apache Kafka. ClickHouse consumes those changes in partial order by Kafka Engine. Real-time and eventually consistent.
- Debezium: Stream Changes from Your Database
What are some alternatives?
timely-dataflow - A modular implementation of timely dataflow in Rust
maxwell - Maxwell's daemon, a mysql-to-json kafka producer
arroyo - Distributed stream processing engine in Rust
kafka-connect-bigquery - A Kafka Connect BigQuery sink connector
2022-bytewax-redpanda-air-quality-monitoring
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
django-unicorn - The magical reactive component framework for Django ✨
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Django - The Web framework for perfectionists with deadlines.
hudi - Upserts, Deletes And Incremental Processing on Big Data.
Pyramid - Pyramid - A Python web framework
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.