Gqlalchemy Alternatives

gqlalchemy reviews and mentions

• Link Prediction With node2vec in Physics Collaboration Network
  4 projects | dev.to | 16 Jun 2023

  As already mentioned, link prediction refers to the task of predicting missing links or links that are likely to occur in the future. In this tutorial, we will make use the of MAGE spell called node2vec. Also, we will use Memgraph to store data, and gqlalchemy to connect from a Python application. The dataset will be similar to the one used in this paper: Graph Embedding Techniques, Applications, and Performance: A Survey.

• Importing Table Data Into a Graph Database With GQLAlchemy
  3 projects | dev.to | 1 Mar 2023

  For any other service provider, it is possible to implement your custom importer class, here's how. Don't forget that GQLAlchemy is an open source project, so you can submit your extended functionality on our GitHub repository.

• How to Become a GQLAlchemist?
  1 project | dev.to | 13 Feb 2023

  If you think there is something crucial that is missing or are even willing the try out your expertise in Python and graphs, check out our GitHub repository and feel free to contribute.

• Monitoring a Dynamic Contact Network With Online Community Detection
  1 project | dev.to | 6 Feb 2023

  gqlalchemy – a Python driver and object graph mapper (OGM)

• Neo4j vs Memgraph - How to choose a graph database?
  4 projects | dev.to | 8 Dec 2022

  There is a broad number of drivers in many different programming languages available for both solutions. While Memgraph only maintains a few in-house drivers that it develops and supports (C, C++, Python, Rust), most Neo4j drivers can also be used with Memgraph. This is due to the fact that both solutions use the Bolt protocol, labeled property graph model and Cypher query language.

• NetworkX Developers, Say Farewell to the Boilerplate Code
  1 project | dev.to | 22 Nov 2022

  Memgraph natively has several methods of data import - import from files, MySQL or PostgreSQL, and data streams. Memgraph is also highly extendable, and with the help of its Python client, GQLAlchemy, you can import data from almost anywhere.

• Retrieve graph data with Python instead of writing Cypher queries
  2 projects | /r/Python | 16 Aug 2022

  Source code for GQLAlchemy is available at GitHub repo.

• [D] Seeking Advice - For graph ML, Neo4j or nah?
  7 projects | /r/MachineLearning | 29 Jul 2022

  I think building your graph database/structure can be quite an engineering and time-consuming challenge, as you mentioned, which I would personally avoid. I believe there are some solutions out there that may help you. There is one open source solution for the requirements and concerns you are mentioning. It checks out most of the things you need, functionality, efficiency, and custom low-level optimizations and it is not bulky as the Neo4j Java backend. In essence, we have built Memgraph an in-memory graph database written in C++. The distinctive key feature of DB is that all the data is stored in RAM for fast queries. There is some cool stuff with ML for graphs. Take a look at this blog post about node embedding and recommendation engines, it is native integration with Python and uses PyTorch. There is also the MAGE library for graph algorithms and ML, it is also open-sourced, which is great news for customization and expansions. I share your thoughts on OpenCypher, as being an issue. Memgraph has an object graph mapper (similar to ORM), called GQLAlchemy, and is in Python. There is also a learning curve, but not a different new skill as Cypher. The good thing is allowed various features for graphs manipulation via Python. There are also some other solutions such TigerGraph, Nebula, etc. But I am not very familiar with them. Feel free to explore. I hope this helps! 😁

• Twitch Streaming Graph Analysis - Part 3
  2 projects | dev.to | 3 Nov 2021

  Using gqlalchemy we are trying to connect to Memgraph, just like we have done before in our backend.

• Twitch Streaming Graph Analysis - Part 1
  3 projects | dev.to | 22 Oct 2021

  As expected, Flask is there, so it will be installed in our container. Next, we have pymgclient, Memgraph database adapter for Python language on top of which gqlalchemy is built. We will connect to the database with gqlalchemy and it will assist us in writing and running queries on Memgraph.

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