Druid
ApacheKafka
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Druid | ApacheKafka | |
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24 | 104 | |
13,188 | 28 | |
0.6% | - | |
9.9 | 0.0 | |
3 days ago | 5 months ago | |
Java | ||
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.
Druid
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How to choose the right type of database
Apache Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence.
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.
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Show HN: The simplest tiny analytics tool – storywise
https://github.com/apache/druid
It's always a question of tradeoffs.
The awesome-selfhosted project has a nice list of open-source analytics projects. It's really good inspiration to dig into these projects and find out about the technology choices that other open-source tools in the space have made.
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Analysing Github Stars - Extracting and analyzing data from Github using Apache NiFi®, Apache Kafka® and Apache Druid®
Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s my analytical pipeline for Github stars data using Nifi, Kafka and Druid.
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Apache Druid® - an enterprise architect's overview
Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications.
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Real Time Data Infra Stack
Apache Druid
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When you should use columnar databases and not Postgres, MySQL, or MongoDB
But then you realize there are other databases out there focused specifically on analytical use cases with lots of data and complex queries. Newcomers like ClickHouse, Pinot, and Druid (all open source) respond to a new class of problem: The need to develop applications using endpoints published on analytical queries that were previously confined only to the data warehouse and BI tools.
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Druids by Datadog
Datadog's product is a bit too close to Apache Druid to have named their design system so similarly.
From https://druid.apache.org/ :
> Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data.
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Mom at 54 is thinking about coding and a complete career shift. Thoughts?
Maybe rare for someone to be seeking their first coding job at that age. But plenty of us are in our 50s or older and still coding up a storm. And not necessarily ancient tech or anything. My current project exposes analytics data from Apache Druid and Cassandra via Go microservices hosted in K8s.
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Building an arm64 container for Apache Druid for your Apple Silicon
Fortunately, it is super easy to build your own leveraging the binary distribution and existing docker.sh.
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?
iced - A cross-platform GUI library for Rust, inspired by Elm
dramatiq - A fast and reliable background task processing library for Python 3.
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications
outbox-inbox-patterns - Repository to support the article "Building a Knowledge Base Service With Neo4j, Kafka, and the Outbox Pattern"
Apache Cassandra - Mirror of Apache Cassandra
Jenkins - Jenkins automation server
Apache HBase - Apache HBase
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
egui - egui: an easy-to-use immediate mode GUI in Rust that runs on both web and native
istio - Connect, secure, control, and observe services.
Scylla - NoSQL data store using the seastar framework, compatible with Apache Cassandra
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.