neo4j
ArangoDB
Redis
OrientDB
MongoDB
Azure Cosmos DB
Apache Cassandra
CouchBase
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
neo4j MatplotlibBased on our record, Matplotlib should be more popular than neo4j. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago
Perhaps the biggest promoter of the term has been Philip Rathle from Neo4j, which offers the best-known graph database system for storing knowledge graphs. But here's where the confusion starts: Is a knowledge graph something you store, or is it how you store something? It's not just a knowledge graphโit's also a graph database. That distinction matters, but the boundaries are blurry. - Source: dev.to / 7 months ago
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 / about 1 year ago
Neo4j is a leading graph database that is easy to use and powerful for knowledge graphs. - Source: dev.to / over 1 year ago
Neo4j is one of the most popular graph databases. It offers powerful querying capabilities through its Cypher query language. - Source: dev.to / over 1 year ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
NumPy - NumPy is the fundamental package for scientific computing with Python
OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
