risingwave
debezium
risingwave | debezium | |
---|---|---|
27 | 80 | |
6,309 | 9,884 | |
2.2% | 1.1% | |
10.0 | 9.9 | |
5 days ago | 3 days ago | |
Rust | 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.
risingwave
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Proton, a fast and lightweight alternative to Apache Flink
How does this compare to RisingWave and Materialize?
https://github.com/risingwavelabs/risingwave
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RisingWave's Roadmap - Redefining Stream Processing with the Rust-Built Streaming Database
Hey everyone - One and a half year ago, we open sourced RisingWave, a Rust-built streaming database, under Apache 2.0 license. Two weeks ago, we released RisingWave 1.3. Just last week, we unveiled RisingWave's roadmap.
- Risingwave: Redefining Stream Processing
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Highlights of RisingWave v1.3: The Open-Source Streaming Database
Look out for next monthโs edition to see what new, exciting features will be added. Check out the RisingWave GitHub repository to stay up to date on the newest features and planned releases.
- Optimizing Rust Code for the Lsm-Tree Iterator in RisingWave
- Hummock: A Storage Engine Designed for Stream Processing
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RisingWave 1.2 released - the open-source streaming database built in Rust
If interested, please feel free to join our Slack community! Thanks eveyone for your generous support!
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Query materialized views with Java, Spring, and streaming database
We will spin up on our local environment the existing RisingWave fully-featured demo cluster on GitHub which is composed of multiple RisingWave components. To simplify this task, it leverages docker-compose.yaml file which includes additional containers for Kafka message broker, and data generation service.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
To complete the steps in this guide, you must download/clone and work on an existing sample project on GitHub. The project uses Docker for convenience and consistency. It provides a containerized development environment that includes the services you need to build the sample data pipeline.
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Flink CDC / alternatives
Hey have you looked at RisingWave (https://github.com/risingwavelabs/risingwave) before? It's a stream processing system with PostgreSQL interface. It also have integrations similar to Flink CDC.
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, itโs 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?
materialize - The data warehouse for operational workloads.
maxwell - Maxwell's daemon, a mysql-to-json kafka producer
datafuse - An elastic and reliable Cloud Warehouse, offers Blazing Fast Query and combines Elasticity, Simplicity, Low cost of the Cloud, built to make the Data Cloud easy [Moved to: https://github.com/datafuselabs/databend]
kafka-connect-bigquery - A Kafka Connect BigQuery sink connector
ksql - The database purpose-built for stream processing applications.
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
greptimedb - An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
chdb - chDB is an embedded OLAP SQL Engine ๐ powered by ClickHouse
hudi - Upserts, Deletes And Incremental Processing on Big Data.
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.