awesome-readme
Apache AGE
Our great sponsors
awesome-readme | Apache AGE | |
---|---|---|
30 | 31 | |
16,961 | 709 | |
- | - | |
6.9 | 8.5 | |
about 17 hours ago | over 1 year ago | |
C | ||
- | 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.
awesome-readme
- Readme: A Curated List of READMEs
- Awesome Readme: A Curated List of READMEs
-
Hacktoberfest 2023 Update from Maintainer of the user-statistician GitHub Action
About user-statistician
-
Hacktoberfest 2023 Contributors Wanted: Additional Translations for the user-statistician GitHub Action
The user-statistician GitHub Action can generate an SVG with a detailed summary of your activity on GitHub. It is mentioned in the tools section of the awesome README awesome list. The SVG it generates includes general information about you (e.g., year you joined, number of followers, number you are following, most starred repository, etc), information about your repositories (e.g., numbers of stars and forks, etc), information about your contributions (e.g., numbers of commits, issues, PRs, etc), and the distribution of languages within your public repositories.
- Mastering Readme Files
-
Marketing for Developers
If you really want a stellar README.md take a look at some of the examples in awesome-readme for inspiration!
-
How to Create the Best README for Your GitHub Project
Awesome README - A collection of high-quality READMEs from a variety of projects, organized by topic. https://github.com/matiassingers/awesome-readme
-
How to create projects for myself to enrich my resume?
Provide a succinct and comprehensive README: readers of your personal project will always start with the README to know where to begin. The goal of the README is to provide the reader an understanding of the business problem you are trying to solve, how your solution goes about solving it (solution architecture diagram), and how to get started and run your code. There are plenty of great README examples here: https://github.com/matiassingers/awesome-readme
-
Configuring GitHub's Linguist to Improve Repository Language Reporting
About user-statistician
-
The user-statistician GitHub Action mentioned in Awesome-README
Recently, the user-statistician GitHub Action was added to the tools section of Awesome README, which is an Awesome List that includes a curated collection of examples of Awesome READMEs from open source projects, as well as tools enabling creating Awesome READMEs. The Awesome README list is a great place to go if you are looking for ideas for how to improve the READMEs of your open source projects. The Awesome README list covers READMEs more generally, but the tools section includes a few tools focused on Profile READMEs, in addition to many tools for project READMEs more generally. The user-statistician GitHub Action is in the Tools Section.
Apache AGE
-
Alternatives to Neo4j Enterprise
What about the AGE extension for Postgres? https://age.apache.org/
-
Anyone Using Graph Databases in F#?
Waiting for Postgres to release theirs.
-
In MongoDB you can have duplicate items even if you have unique index
I think they are talking about the AGE extension https://age.apache.org
-
Age 1.0 – PostgreSQL extension for graph database
It's my understanding of the "incubation" period of Apache Software Foundation projects is to determine if they're able to actually execute the ASF process, and a bunch of other "project maturity metrics" (https://community.apache.org/apache-way/apache-project-matur...) of which AGE currently has some self-certification: https://age.apache.org/?l=maturity#
I recognize that's not exactly an answer to the question you asked, but I would be surprised if someone other than a project member knows a more forward-looking one
-
Looking for opinions: 95% of my Data fits extremely well in a Relational Database and 5% fits extremely well into a graph database. Should I consider splitting it between the two, or is that a silly idea?
Postgres has a graph extension: https://age.apache.org. This means you can keep all your data in PG and use both models.
-
Getting Started with Redis and RedisGraph
PostgreSQL with graph extension, developed by a team at Apache Software Foundation as Apache AGE. Apache AGE uses Gremlin.
-
Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
The big thing that graph dbs provide is transitive traversals of join relationships.
The problem with graph dbs is trying to return something that is not a graph. Like a count. Or derived information. And which graph model do you use? There’s more than one. Lots of information is very poorly modeled in graph dbs. Temporal organization, for example.
Ultimately, graphs are a way to use relations. But relations allow you much more flexibility to associate information (subject to the issue of transitive relationship traversal).
Mixed graph-relational is perfectly reasonable. Reasonable start here: [https://age.apache.org/]
their actual landing page is actually better than the Github one. It's a translation layer(s) to allow querying Postgres using openCypher
-
Truth Behind Neo4j’s “Trillion” Relationship Graph
Depending on how one views "postgres", there are at least two extensions that allegedly do it: https://age.apache.org/ and the AgensGraph from which AGE derives
-
One table vs two table design
There's an extension to postgresql (I haven't used it, but I am familiar with node/edge tables in MSSQL) that allows you to do this: https://age.apache.org/
What are some alternatives?
revo-grid - Powerful virtual data grid smartsheet with advanced customization. Best features from excel plus incredible performance 🔋
Neo4j - Graphs for Everyone
Konva - Konva.js is an HTML5 Canvas JavaScript framework that extends the 2d context by enabling canvas interactivity for desktop and mobile applications.
janusgraph - JanusGraph: an open-source, distributed graph database
amplify-cli - The AWS Amplify CLI is a toolchain for simplifying serverless web and mobile development.
RedisGraph - A graph database as a Redis module
spring-rest-crud-example - Use this repository as a basis to start the development of a new Java REST API.
yugabyte-db - YugabyteDB - the cloud native distributed SQL database for mission-critical applications.
minio-py - MinIO Client SDK for Python
datalevin - A simple, fast and versatile Datalog database
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
datahike - A durable Datalog implementation adaptable for distribution.