Ananas Analytics Desktop vs Looker

Overview

Looker

Stacks632

Followers656

Votes9

Ananas Analytics Desktop

Stacks0

Followers11

Votes0

GitHub Stars578

Forks43

Ananas Analytics Desktop vs Looker: What are the differences?

Ananas Analytics Desktop: *A hackable data integration/analysis tool *. It is a hackable data integration & analysis tool to enable non technical users to edit data processing jobs and visualise data on demand. You can connect data from anywhere. Transform, analyze, and visualize with simple steps; Looker: Pioneering the next generation of BI, data discovery & data analytics. We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.

Ananas Analytics Desktop and Looker belong to "Business Intelligence" category of the tech stack.

Some of the features offered by Ananas Analytics Desktop are:

Built for Non-technical User
Powered by SQL
Offline Mode

On the other hand, Looker provides the following key features:

Zero-lag access to data
No limits
Personalized setup and support

Ananas Analytics Desktop is an open source tool with 365 GitHub stars and 17 GitHub forks. Here's a link to Ananas Analytics Desktop's open source repository on GitHub.

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CLI (Node.js)

Manual

Advice on Looker, Ananas Analytics Desktop

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k

Comments

Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k

Comments

Detailed Comparison

Looker	Ananas Analytics Desktop
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.	It is a hackable data integration & analysis tool to enable non technical users to edit data processing jobs and visualise data on demand. You can connect data from anywhere. Transform, analyze, and visualize with simple steps.
Zero-lag access to data;No limits;Personalized setup and support;No uploading, warehousing, or indexing;Deploy anywhere;Works in any browser, anywhere;Personalized access points	Built for Non-technical User; Powered by SQL; Offline Mode; Comes with technical tools for engineers to test, and run Ananas data projects in cloud or on premise
Statistics
GitHub Stars -	GitHub Stars 578
GitHub Forks -	GitHub Forks 43
Stacks 632	Stacks 0
Followers 656	Followers 11
Votes 9	Votes 0
Pros & Cons
Pros 4 Real time in app customer chat support 4 GitHub integration 1 Reduces the barrier of entry to utilizing data Cons 3 Price	No community feedback yet
Integrations
No integrations available	PostgreSQL MySQL Google Cloud Storage Google BigQuery Google Cloud SQL JSON

What are some alternatives to Looker, Ananas Analytics Desktop?

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'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: 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

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

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

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

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 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

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.

Related Comparisons

Some of the features offered by Ananas Analytics Desktop are:

Built for Non-technical User
Powered by SQL
Offline Mode

On the other hand, Looker provides the following key features:

Zero-lag access to data
No limits
Personalized setup and support

Ananas Analytics Desktop is an open source tool with 365 GitHub stars and 17 GitHub forks. Here's a link to Ananas Analytics Desktop's open source repository on GitHub.

Ananas Analytics Desktop vs Looker