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  1. Stackups
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  3. Monitoring
  4. Monitoring Tools
  5. Pixi vs Skedler

Pixi vs Skedler

OverviewComparisonAlternatives

Overview

Pixi
Pixi
Stacks100
Followers86
Votes8
Skedler
Skedler
Stacks0
Followers3
Votes0

Pixi vs Skedler: What are the differences?

# Introduction

Pixi and Skedler are both popular visualization tools that offer various features to help users create dynamic and interactive reports. 

1. **Data Source Integration**: Pixi supports a wide range of data sources including SQL databases, CSV files, and APIs, while Skedler focuses primarily on integrating with Elasticsearch, enabling users to leverage its powerful search and analytics capabilities.
2. **Customization Options**: Pixi provides extensive customization options for graphs, charts, and dashboards, allowing users to tailor their visualizations to specific needs. Skedler, on the other hand, offers a more streamlined approach with predefined templates for quick and easy report generation.
3. **Real-time Data Visualization**: Pixi excels in real-time data visualization capabilities, enabling users to monitor and analyze live data streams effectively. Skedler, however, is more suited for batch processing and scheduled reporting, providing a more structured approach to data visualization.
4. **Component Library**: Pixi offers a rich library of components and plugins that users can leverage to enhance their visualizations, while Skedler focuses on providing a concise set of essential components to streamline the reporting process.
5. **Collaboration Features**: Pixi provides robust collaboration features, allowing multiple users to work on a visualization project simultaneously and share feedback in real-time. Skedler offers limited collaboration functionality, focusing more on individual report generation and distribution.
6. **Cost Structure**: Pixi follows a subscription-based pricing model with tiered plans based on user requirements, while Skedler offers a more straightforward pricing structure with a one-time purchase option, making it a cost-effective solution for organizations with specific reporting needs.

In Summary, Pixi and Skedler offer distinct differences in terms of data integration, customization options, real-time visualization capabilities, component libraries, collaboration features, and cost structures, catering to a range of user preferences and requirements.

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Detailed Comparison

Pixi
Pixi
Skedler
Skedler

Super fast HTML 5 2D rendering engine that uses webGL with canvas fallback

It is an elasticsearch reporting tool --- an absolute alternative to Kibana reporting. It enables you to automate the whole process of designing, scheduling, and delivering reports to your stakeholders/ customers effectively.

Multi-platform Support;Interactive, visually compelling content on desktop, mobile and beyond, all reached with a single codebase to deliver transferable experiences;Tinting & Blending Modes;Sprite Sheet Support;Asset Loader;Easy API;WebGL Filters
Automated Reporting; Elasticsearch report scheduling; Automated elasticsearch report delivery through email, Slack, and more
Statistics
Stacks
100
Stacks
0
Followers
86
Followers
3
Votes
8
Votes
0
Pros & Cons
Pros
  • 8
    Fast Performance
No community feedback yet
Integrations
HTML5
HTML5
React
React
WebGL
WebGL
Docker
Docker
Elasticsearch
Elasticsearch
Linux
Linux
Windows
Windows
Debian
Debian

What are some alternatives to Pixi, Skedler?

Grafana

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Kibana

Kibana

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Prometheus

Prometheus

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Nagios

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

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