k8ssandra
ApacheKafka
k8ssandra | ApacheKafka | |
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3 | 104 | |
422 | 28 | |
0.5% | - | |
6.3 | 0.0 | |
20 days ago | 5 months ago | |
YAML | ||
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.
k8ssandra
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How the world caught up with Apache Cassandra
Twelve-plus years after its invention, Cassandra is now used by approximately 90 percent of the Fortune 100, and it’s appeal is broadening quickly, driven by a rush to harness today’s “data deluge” with apps that are globally distributed and always-on. Add to this recent advances in the Cassandra ecosystem such as Stargate, K8ssandra, and cloud services like Astra DB, and the cost and complexity barriers to using Cassandra are fading into the past. So while it’s fair to say that while Cassandra might have been ahead of its time in 2007, it’s primed and ready for the data demands of the 2020s and beyond.
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Why a Cloud-Native Database Must Run on K8s
For this reason, there has been a surge of recent interest in data infrastructure that is designed to take maximum advantage of the benefits that cloud computing provides. A cloud-native database is one that achieves the goals of scalability, elasticity, resiliency, observability and automation; the K8ssandra project is a great example. It packages Apache Cassandra and supporting tools into a production-ready Kubernetes deployment.
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Kubernetes Data Simplicity: Getting started with K8ssandra
``You might have heard about the K8ssandra project and want to start contributing, or maybe you want to start using all of its features. If you aren’t familiar with K8ssandra (pronounced like “Kate Sandra”), you can read this overview before digging into the developer activities in this post.
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?
cass-operator - The DataStax Kubernetes Operator for Apache Cassandra
dramatiq - A fast and reliable background task processing library for Python 3.
medusa-operator - A Kubernetes operator for managing Cassandra backups/restores with Medusa
outbox-inbox-patterns - Repository to support the article "Building a Knowledge Base Service With Neo4j, Kafka, and the Outbox Pattern"
cassandra-reaper - Automated Repair Awesomeness for Apache Cassandra
Jenkins - Jenkins automation server
cassandra-medusa - Apache Cassandra Backup and Restore Tool
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
Visual Studio Code - Visual Studio Code
istio - Connect, secure, control, and observe services.
helm - The Kubernetes Package Manager
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.