neo4j Reviews

NetworkX Reviews

neo4j mentions (34)

• 6 retrieval augmented generation (RAG) techniques you should know

  The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill. - Source: dev.to / 6 days ago

• LLM to extract and auto generate knowledge graph - step by step, in ~100 lines of python

  Neo4j is a leading graph database that is easy to use and powerful for knowledge graphs. - Source: dev.to / 8 days ago

• 10 Ways AI Can Speed Up your Mobile App Development

  Neo4j is one of the most popular graph databases. It offers powerful querying capabilities through its Cypher query language. - Source: dev.to / 2 months ago

• Databases in 2024: A Year in Review

  Great heads up. I wonder about graph databases. He mentioned and both include the graph use case and I wonder how they compare to . - Source: Hacker News / 4 months ago

• Installing Neo4j In Ubuntu

  The first blog in this series is to install neo4j - desktop version and few plugins which would help us to build an application. I am using Ubuntu 22.04.4 LTS. - Source: dev.to / 9 months ago

NetworkX mentions (35)

• Representing Graphs in PostgreSQL

  If you are interested in the subject, also take a look at NetworkDisk[1] which enable users of NetworkX[2] which maps graphs to databases. [1] https://networkdisk.inria.fr/ [2] https://networkx.org/. - Source: Hacker News / 2 months ago

• Build the dependency graph of your BigQuery pipelines at no cost: a Python implementation

  In the project we used Python lib networkx and a DiGraph object (Direct Graph). To detect a table reference in a Query, we use sqlglot, a SQL parser (among other things) that works well with Bigquery. - Source: dev.to / over 1 year ago

• Custom libraries and utility tools for challenges

  If you program in Python, can use NetworkX for that. But it's probably a good idea to implement the basic algorithms yourself at least one time. Source: over 1 year ago

• Google open-sources their graph mining library

  For those wanting to play with graphs and ML I was browsing the arangodb docs recently and I saw that it includes integrations to various graph libraries and machine learning frameworks [1]. I also saw a few jupyter notebooks dealing with machine learning from graphs [2]. Integrations include: * NetworkX -- https://networkx.org/ * DeepGraphLibrary -- https://www.dgl.ai/ * cuGraph (Rapids.ai Graph) --... - Source: Hacker News / over 1 year ago

• org-roam-pygraph: Build a graph of your org-roam collection for use in Python

  Org-roam-ui is a great interactive visualization tool, but its main use is visualization. The hope of this library is that it could be part of a larger graph analysis pipeline. The demo provides an example graph visualization, but what you choose to do with the resulting graph certainly isn't limited to that. See for example networkx. Source: almost 2 years ago