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  5. Chartio vs FnordMetric

Chartio vs FnordMetric

OverviewComparisonAlternatives

Overview

Chartio
Chartio
Stacks631
Followers116
Votes6
FnordMetric
FnordMetric
Stacks4
Followers15
Votes0

Chartio vs FnordMetric: What are the differences?

  1. Data Sources: Chartio supports a wide range of data sources such as databases, SaaS services, and cloud storage, making it a versatile tool for data visualization. On the other hand, FnordMetric is specifically designed for time-series data, making it ideal for monitoring and analyzing real-time metrics.

  2. Customization and Embedding: Chartio provides advanced customization options for creating tailored dashboards and reports, and also allows easy embedding of visualizations into websites and apps. Contrary to this, FnordMetric focuses on providing a simple and streamlined interface, without extensive customization features or embedding capabilities.

  3. Collaboration Tools: Chartio offers collaboration features like team sharing, commenting, and real-time editing of dashboards, fostering team collaboration and communication. In contrast, FnordMetric lacks these robust collaboration tools, focusing more on individual data analysis and visualization tasks.

  4. Security and Compliance: Chartio prioritizes data security and compliance by providing features like role-based access control, data encryption, and compliance with regulations like GDPR. FnordMetric lacks comprehensive security and compliance features, which may be a concern for organizations dealing with sensitive data.

  5. Price Structure: Chartio follows a tiered pricing structure based on user numbers and features, allowing scalability and flexibility for different business needs. FnordMetric, on the other hand, offers a more straightforward pricing model with a one-time payment for the software, making it a more cost-effective option for some users.

  6. Learning Curve: Chartio provides a user-friendly interface and rich documentation, making it easier for users to learn and navigate the tool without significant training or technical expertise. In comparison, FnordMetric may have a steeper learning curve due to its focus on time-series data and specialized functionalities.

In Summary, the key differences between Chartio and FnordMetric lie in their support for data sources, customization options, collaboration tools, security features, pricing structures, and learning curves.

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Detailed Comparison

Chartio
Chartio
FnordMetric
FnordMetric

Chartio is a cloud-based business analytics solution on a mission to enable everyone within an organization to access, explore, transform and visualize their data.

FnordMetric allows you to write SQL queries that return SVG charts rather than tables. Turning a query result into a chart is literally one line of code. FnordMetric allows you collect and visualize timeseries data using only SQL. It enables you to build beautiful real-time analytics dashboards within minutes.

Direct connections to your data warehouse or database (Redshift, BigQuery, Snowflake, Postgres, MySQL and many more); Intuitive drag-and-drop interface for data exploration with Visual SQL as well as direct SQL interface; Powerful data pipeline for data transformations; Interactive dashboards with rich visualizations and filters; Easy collaboration and sharing of charts, reports and dashboards; Alerts and notifications
Line Charts;Area Charts;Bar Charts;Bubble & Scatter Charts;Combined Charts;Metric collection;Local Disk Backend;Send metric data to FnordMetric Server using a simple HTTP interface;Send metric data using the statsd protocol
Statistics
Stacks
631
Stacks
4
Followers
116
Followers
15
Votes
6
Votes
0
Pros & Cons
Pros
  • 2
    Affordable for a BI solution
  • 2
    Join multiple databases
  • 2
    Great UI
No community feedback yet

What are some alternatives to Chartio, FnordMetric?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

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