AtScale vs Metabase

Overview

Metabase

Stacks926

Followers1.2K

Votes271

GitHub Stars44.4K

Forks6.0K

AtScale

Stacks25

Followers83

Votes0

Metabase vs AtScale: What are the differences?

Developers describe Metabase as "An open-source business intelligence tool". Metabase 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. On the other hand, AtScale is detailed as "The virtual data warehouse for the modern enterprise". Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics.

Metabase and AtScale belong to "Business Intelligence" category of the tech stack.

Metabase is an open source tool with 16.6K GitHub stars and 2.2K GitHub forks. Here's a link to Metabase's open source repository on GitHub.

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CLI (Node.js)

Manual

Detailed Comparison

Metabase	AtScale
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.	Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics.
-	Multiple SQL-on-Hadoop Engine Support; Access Data Where it Lays; Built-in Support for Complex Data Types; Single Drop-in Gateway Node Deployment
Statistics
GitHub Stars 44.4K	GitHub Stars -
GitHub Forks 6.0K	GitHub Forks -
Stacks 926	Stacks 25
Followers 1.2K	Followers 83
Votes 271	Votes 0
Pros & Cons
Pros 62 Database visualisation 45 Open Source 41 Easy setup 36 Dashboard out of the box 23 Free Cons 7 Harder to setup than similar tools	No community feedback yet
Integrations
PostgreSQL MongoDB Amazon Redshift MySQL Microsoft SQL Server	Python Amazon S3 Tableau Power BI Qlik Sense Azure Database for PostgreSQL

What are some alternatives to Metabase, AtScale?

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

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.

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

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.

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.