Neo4j
ApacheKafka
Neo4j | ApacheKafka | |
---|---|---|
49 | 104 | |
12,454 | 28 | |
1.5% | - | |
9.9 | 0.0 | |
7 days ago | 5 months ago | |
Java | ||
GNU General Public License v3.0 only | - |
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.
Neo4j
-
How to choose the right type of database
Neo4j: An ACID-compliant graph database with a high-performance distributed architecture. Ideal for complex relationship and pattern analysis in domains like social networks.
-
Looks Like the Free Software Foundation Forced Neo4j's Hand
After spending millions fighting the committer of ONgDB who removed the commons clause from the AGPL branded license, it looks like the Free Software Foundation got involved and forced them to remove the commons clause or change the license to their own proprietary license.
https://github.com/neo4j/neo4j/commit/b6237ca4e31706b1efbd0f...
-
Getting Started with GenAI Stack powered with Docker, LangChain, Neo4j and Ollama
The GenAI Stack came about through a collaboration between Docker, Neo4j, LangChain, and Ollama. The goal of the collaboration was to create a pre-built GenAI stack of best-in-class technologies that are well integrated, come with sample applications, and make it easy for developers to get up and running. The goal of the collaboration was to create a pre-built GenAI stack of best-in-class technologies that are well integrated, come with sample applications, and make it easy for developers to get up and running.
-
Database Review: Top Five Missing Features from Database APIs
Neo4j (GraphQL)
-
How to Choose the Right Document-Oriented NoSQL Database for Your Application
NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and Cassandra.
-
Loading data
this thread on this github issue could be useful.
-
[For Hire] Senior Developer with 14 years experience. Canadian expat in a low cost of living country | From 500 EUR per project/month
Recently I have taken an interest in big data. https://neo4j.com/ , https://cassandra.apache.org/ , https://clickhouse.com/, https://www.elastic.co/ - are all databases I have experience with. Neo4j and Cassandra only as a hobby, but Clickhouse I have used in production, and Elasticsearch I have used for some 7 years now.
-
SQL Versus NoSQL Databases: Which to Use, When, and Why
For organizations and their applications that are designed to detect fraud, like International Consortium of Investigative Journalists, or try to improve customer experience via personalization, as in the case of Tourism Media, a NoSQL graph database like Neo4j is a good match. In these kinds of use cases, the quantity of data we're dealing with is enormous, and the pattern we're searching for in the data is often complex.
-
Graph Databases vs Relational Databases: What and why?
First, you need to choose a specific graph database platform to work with, such as Neo4j, OrientDB, JanusGraph, Arangodb or Amazon Neptune. Once you have selected a platform, you can then start working with graph data using the platform's query language.
-
The Basics of Querying with Cypher in PostgreSQL using Apache Age
Welcome to the world of graph databases! When it comes to modelling complex and highly connected data, graph databases have proven to be an efficient and intuitive solution. And one of the most popular graph databases out there is Neo4j, which uses a query language called Cypher.
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
-
Wie man Ereignisse von PubNub zu RabbitMQ streamt
Senden an Kafka (d. h. Senden der Daten an Apache Kafka)
-
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.
-
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.
-
🦿🛴Smarcity garbage reporting automation w/ ollama
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...)
-
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.
-
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.
-
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?
Apache AGE - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL. [Moved to: https://github.com/apache/age]
dramatiq - A fast and reliable background task processing library for Python 3.
Hasura - Blazing fast, instant realtime GraphQL APIs on your DB with fine grained access control, also trigger webhooks on database events.
outbox-inbox-patterns - Repository to support the article "Building a Knowledge Base Service With Neo4j, Kafka, and the Outbox Pattern"
FlockDB - A distributed, fault-tolerant graph database
Jenkins - Jenkins automation server
RedisGraph - A graph database as a Redis module
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
ArangoDB - 🥑 ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.
istio - Connect, secure, control, and observe services.
janusgraph - JanusGraph: an open-source, distributed graph database
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.