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MapD

9
24
+ 1
4
Tableau

917
954
+ 1
5
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MapD vs Tableau: What are the differences?

MapD: Open source GPU-Powered Database. Interactively query and visualize massive datasets with the parallel power of GPUs; Tableau: Tableau helps people see and understand data. Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

MapD and Tableau are primarily classified as "Databases" and "Business Intelligence" tools respectively.

Some of the features offered by MapD are:

  • SQL
  • GPU-powered
  • column store

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

  • Connect to data on prem or in the cloud—whether it’s big data, a SQL database, a spreadsheet, or cloud apps like Google Analytics and Salesforce. Access and combine disparate data without writing code. Power users can pivot, split, and manage metadata to optimize data sources. Analysis begins with data. Get more from yours with Tableau.
  • Exceptional analytics demand more than a pretty dashboard. Quickly build powerful calculations from existing data, drag and drop reference lines and forecasts, and review statistical summaries. Make your point with trend analyses, regressions, and correlations for tried and true statistical understanding. Ask new questions, spot trends, identify opportunities, and make data-driven decisions with confidence.
  • Answer the “where” as well as the “why.” Create interactive maps automatically. Built-in postal codes mean lightning-fast mapping for more than 50 countries worldwide. Use custom geocodes and territories for personalized regions, like sales areas. We designed Tableau maps specifically to help your data stand out.

MapD is an open source tool with 1.91K GitHub stars and 271 GitHub forks. Here's a link to MapD's open source repository on GitHub.

Decisions about MapD and Tableau

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.

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Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 165.4K views

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.

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Pros of MapD
Pros of Tableau
  • 3
    Super fast, and the approach taken
  • 1
    Hehe
  • 4
    Capable of visualising billions of rows
  • 1
    Responsive

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- No public GitHub repository available -

What is MapD?

Interactively query and visualize massive datasets with the parallel power of GPUs.

What is Tableau?

Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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What companies use MapD?
What companies use Tableau?
See which teams inside your own company are using MapD or Tableau.
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What tools integrate with MapD?
What tools integrate with Tableau?

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What are some alternatives to MapD and Tableau?
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.
Clickhouse
It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
See all alternatives