Apache AGE
quine
| Apache AGE | quine | |
|---|---|---|
| 132 | 6 | |
| 2,695 | 282 | |
| 3.6% | 3.2% | |
| 8.9 | 9.4 | |
| 5 days ago | about 19 hours ago | |
| C | Scala | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
Apache AGE
- Apache AGE: PostgreSQL Extension Graph Data Processing and Analytics
- Apache AGE: PostgreSQL Extension Graph Data Processing and Analytics for RDBMS
- Apache AGE supporting latest PostgreSQL (ver 16)
-
Enhancing Fraud Detection with Apache AGE: A Graph Database Approach
For more information and support, visit the Apache AGE website. or github.
-
Unlocking the Power of Apache Age: Advanced Techniques for SQL/Cypher Hybrid Queries
These are just a few examples of how you can use Cypher queries in SQL/Cypher Hybrid Queries. By using these advanced techniques, you can perform more complex and powerful queries on your graph data. Apache AGE offer a versatile and powerful platform for working with graph and relational data concurrentlyz. To learn more you can visit age website or github page.
-
Mastering Graph Queries with Cypher in Apache Age
Cypher queries in Apache Age empower users to interact with graph data efficiently and intuitively. Whether you're creating nodes, establishing relationships, or performing complex traversals, Cypher provides a robust and expressive language for working with graph databases.As you explore Apache Age and Cypher further, you'll discover additional features and nuances that make graph database management a seamless experience. Embrace the power of graph queries, and unlock the full potential of your interconnected data with Apache Age. Happy graph querying!
- We built An Open-Source platform to process relational and Graph Query simultaneously
-
Machine learning and graph databases
Check Apache AGE graph database system here: Website: https://age.apache.org/ GitHub: https://github.com/apache/age
- Is Open Sourcing Technologies Good for Society
-
Open Source doesn't win by being cheaper
We are also open Source community at Apache https://github.com/apache/age
quine
-
Create a Quine Icon Library with Python
Quine
-
Postgres: The Graph Database You Didn't Know You Had
Re [5]'s asssertion under "blunders" of the diminish usecases post sql/pgq, what do you think of sometime like Quine?
https://github.com/thatdot/quine
Their claim to fame is progressive incremental computation - each node is an actor responding to events -- and I'm not sure how a relational db could do that and match the latencies. That usecase is pretty much pattern matching and forensics and stuff like that.
https://docs.quine.io/core-concepts/architecture.html
-
Use Quine Graph ETL to reduce SIEM storage costs.
Download Quine - JAR file | Docker Image | Github
-
Standing Queries: Turning Data-Driven Events into Event-Driven Data
The first step to making a Standing Query is determining the graph pattern you want to watch for. You may have deployed Quine in your data pipeline to perform a series of tasks to isolate data, implement a specific feature, or monitor the stream to find a specific pattern in real time. In any case, Quine will implement your logic using Cypher. The recipe for this example is included in the Quine repo if you'd like to follow along.
-
Ingesting From Multiple Data Sources into Quine Streaming Graphs
Quine is open source if you want to run this analysis for yourself. Download a precompiled version or build it yourself from the codebase (Quine Github). I published the recipe that I developed at https://quine.io/recipes. The page has instructions for downloading the CSV files and running the recipe.
-
Ingesting Internet Data into Quine Streaming Graph
I welcome your feedback! Drop in to Quine Slack and let me know what you think. I'm always happy to discuss Quine or answer questions.
What are some alternatives?
surrealdb - A scalable, distributed, collaborative, document-graph database, for the realtime web
lila-ws - Lichess' websocket server
node-bindgen - Easy way to write Node.js module using Rust
AkkaGRPC - Akka gRPC
Memgraph - Open-source graph database, tuned for dynamic analytics environments. Easy to adopt, scale and own.
Scala Graph - Graph for Scala is intended to provide basic graph functionality seamlessly fitting into the Scala Collection Library. Like the well known members of scala.collection, Graph for Scala is an in-memory graph library aiming at editing and traversing graphs, finding cycles etc. in a user-friendly way.
age-viewer - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL.
fs2-kafka - Functional Kafka Streams for Scala
napi-rs - A framework for building compiled Node.js add-ons in Rust via Node-API
Iteratee - Iteratees for Cats
neon - Rust bindings for writing safe and fast native Node.js modules.
ldbc_snb_bi - Reference implementations for the LDBC Social Network Benchmark's Business Intelligence (BI) workload