Warp 10
InfluxData
MetricsGraphics.js
TimescaleDB
QuestDB
Quickmetrics
amCharts
Prometheus
Plotly
D3.js
Chart.js
Highcharts
Google Charts
RAWGraphs
Tableau
Microsoft Power BI
Warp 10 is a modular open source platform that collects, stores and analyzes data from sensors. Shaped for the Internet of Things (IoT) with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database (TSDB) and a powerful analysis environment. The two components can be used together or independently. The Warp 10 Analytics Engine is based on a library of more than 1300 functions adapted to time series and on two analysis languages, WarpScript and FLoWS. This environment makes it possible in particular to perform statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter or Zeppelin. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system. Whatever your business, your data or your processes, Warp 10 fits your needs at any scale.
PlotlyBased on our record, Plotly seems to be more popular. It has been mentiond 29 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.
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: 11 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
InfluxData - Scalable datastore for metrics, events, and real-time analytics.
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.
MetricsGraphics.js - D3-based library optimized for visualizing time-series data
Chart.js - Easy, object oriented client side graphs for designers and developers.
TimescaleDB - TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
