Karafka
ApacheKafka
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Karafka | ApacheKafka | |
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3 | 104 | |
1,972 | 28 | |
2.7% | - | |
9.6 | 0.0 | |
4 days ago | 5 months ago | |
Ruby | ||
Creative Commons Attribution Non Commercial 2.5 Generic | - |
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.
Karafka
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ruby-kafka has been officially deprecated and is no longer recommended for production usage
It is no longer recommended for production usage. If you use it, you can either switch to rdkafka-ruby or one of high-level libraries like karafka.
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Event Streaming in Rails with Kafka
Karafka is a framework used to simplify Apache Kafka-based Ruby applications development.
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Code Loaders in Ruby: Understanding Zeitwerk
Karafka
ApacheKafka
- PubNubとIFTTTによるSMS通知システム
- PubNub 및 IFTTT를 사용한 SMS 알림 시스템
- Système de notification par SMS avec PubNub et IFTTT
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Wie man Ereignisse von PubNub zu RabbitMQ streamt
Senden an Kafka (d. h. Senden der Daten an Apache Kafka)
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.
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How to Use Reductstore as a Data Sink for Kafka
Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time.
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🦿🛴Smarcity garbage reporting automation w/ ollama
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...)
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How to Build & Deploy Scalable Microservices with NodeJS, TypeScript and Docker || A Comprehesive Guide
RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput.
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Easy Guide to Integrating Kafka: Practical Solutions for Managing Blob Data
Apache Kafka is a distributed streaming platform to share data between applications and services in real-time.
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Go concurrency simplified. Part 4: Post office as a data pipeline
also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.
What are some alternatives?
Sidekiq - Simple, efficient background processing for Ruby
dramatiq - A fast and reliable background task processing library for Python 3.
ruby-kafka - A Ruby client library for Apache Kafka
outbox-inbox-patterns - Repository to support the article "Building a Knowledge Base Service With Neo4j, Kafka, and the Outbox Pattern"
Shoryuken - A super efficient Amazon SQS thread based message processor for Ruby
Jenkins - Jenkins automation server
Delayed::Job - Database based asynchronous priority queue system -- Extracted from Shopify
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
librdkafka - The Apache Kafka C/C++ library
istio - Connect, secure, control, and observe services.
Bunny - Bunny is a popular, easy to use, mature Ruby client for RabbitMQ
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.