kafka-service
debezium
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| kafka-service | debezium | |
|---|---|---|
| 4 | 80 | |
| 7 | 9,843 | |
| - | 1.8% | |
| 0.0 | 9.9 | |
| about 1 year ago | 4 days ago | |
| Java | Java | |
| MIT License | 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.
kafka-service
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[SHOWOFF SATURDAY] Kafka Service - An HTTP based client for testing Kafka Clusters.
To use, make a POST request to Kafka Service APIs and let it take over from there. Use handlebars to template your payload, generate random strings, numbers, UUIDs, timestamps etc., or encode/decode strings and more. For details, visit Wiki
- Kafka Service: A HTTP based client to test Kafka Clusters
- Kafka Service: A HTTP based client for testing Kafka Clusters
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?
kafka-connect-file-pulse - 🔗 A multipurpose Kafka Connect connector that makes it easy to parse, transform and stream any file, in any format, into Apache Kafka
maxwell - Maxwell's daemon, a mysql-to-json kafka producer
java-kafka-client - OpenTracing Instrumentation for Apache Kafka Client
kafka-connect-bigquery - A Kafka Connect BigQuery sink connector
wafka - Apache Kafka API exposed through WebSocket and REST protocols
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
kafka-java-spring-boot-poc - Kafka integration with Java Spring-boot with one application serving as a producer and the other consuming the messages
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
sample-spring-kafka-microservices - Example microservices showing how to use Kafka and Kafka Streams with Spring Boot on the example of distributed transactions implementations with the SAGA pattern
hudi - Upserts, Deletes And Incremental Processing on Big Data.
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.
iceberg - Apache Iceberg