Memgraph
neo4j
FalkorDB
ArangoDB
TigerGraph DB
RedisGraph
DBeaver
Serverless Headless CMS by Webiny
Plotly
D3.js
Chart.js
Highcharts
RAWGraphs
Google Charts
Tableau
Microsoft Power BI
Memgraph is a streaming graph application platform that helps you wrangle your streaming data, build sophisticated models that you can query in real-time, and develop applications you never thought possible in days, not months.
Memgraph directly connects to your streaming infrastructure, so you and your team don’t spend countless hours building and maintaining complex data pipelines. You can ingest data from sources like Kafka, SQL, or plain CSV files. Memgraph provides a standard interface to query your data with Cypher, a widely-used and declarative query language that is easy to write, understand and optimize for performance. This is achieved by using the property graph data model, which stores data in terms of objects, their attributes, and the relationships that connect them. This is a natural and effective way to model many real-world problems without relying on complex SQL schemas.
Memgraph is implemented in C/C++ and leverages an in-memory first architecture to ensure that you’re getting the best possible performance consistently and without surprises. It’s also ACID-compliant and highly available.
Memgraph PlotlyNo features have been listed yet.
The product is very robust and easy to use. I highly recommend it to anyone who needs to analyze streaming data in real-time.
Plotly might be a bit more popular than Memgraph. We know about 29 links to it since March 2021 and only 21 links to Memgraph. 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.
Memgraph | Staff C++ Database Engineer | REMOTE (Central/Western Europe, LatAm, or North America) https://memgraph.com/ Memgraph is a Seed stage, open source graph database vendor. Graph DBs are a great solution for GenAI, logistics, cybersecurity and fintech so we are looking to grow aggressively this year. We're looking for a staff-level engineer to set technical direction, mentor junior team members, and solve... - Source: Hacker News / 2 months ago
Relational databases have a much longer history of development, and much more engineering time has went into designing RDBMS. It is not a surprise that they are mature on more levels. By looking at the age of a product, you can get a sense of how mature RDBMS systems are compared to most GraphDB projects. Horizontal scaling is hard in GraphDBs due to the nature of how the graph is structured and how you interact... - Source: Hacker News / 5 months ago
NoSQL databases are non-relational databases with flexible schema designed for high performance at a massive scale. Unlike traditional relational databases, which use tables and predefined schemas, NoSQL databases use a variety of data models. There are 4 main types of NoSQL databases - document, graph, key-value, and column-oriented databases. NoSQL databases generally are well-suited for unstructured data,... - Source: dev.to / 10 months ago
Whether it's about identifying similar user profiles in a social network, detecting similar patterns in a communication network, or classifying nodes in a semantic network, cosine similarity contributes valuable insights. Combined with a powerful graph database system, such as Memgraph, it gives a better understanding of complex networks. Memgraph is an open-source in-memory graph database built to handle... - Source: dev.to / 11 months ago
Take a look at this blog post about choosing the optimal index. It focuses on Memgraph graph database but it offers a theoretical background that is not vendor related. Source: about 1 year ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 5 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: 12 months ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 12 months ago
I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: about 1 year ago
Plotly Dash is a great framework for developing interactive data dashboards using Python, R, and Javascript. It works alongside Plotly to bring your beautiful visualizations to the masses. - Source: dev.to / over 1 year ago
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
FalkorDB - Explore FalkorDB, the premier knowledge graph database tailor-made for GenAI applications. Unlock the power of structured data for advanced AI insights.
Chart.js - Easy, object oriented client side graphs for designers and developers.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
