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AtScale
AtScale

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Cumul.io
Cumul.io

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AtScale vs Cumul.io: What are the differences?

AtScale: 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; Cumul.io: The building block for dashboards in your platform. Create powerful dashboards in minutes. Share with your teams, or integrate in your platform. Drive growth in your business today!

Designing great graphs quick, like Klipfolio, but easier Many datasource plugins.

AtScale belongs to "Big Data Tools" category of the tech stack, while Cumul.io can be primarily classified under "Business Dashboards".

Some of the features offered by AtScale are:

  • Multiple SQL-on-Hadoop Engine Support
  • Access Data Where it Lays
  • Built-in Support for Complex Data Types

On the other hand, Cumul.io provides the following key features:

  • Drag & drop Excel sheets, CSV, TSV, GeoJSON, TopoJSON or other spreadsheet files.
  • Easy-to-use API
  • Build your own integration with our powerful API
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What is AtScale?

Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics.

What is Cumul.io?

Create powerful dashboards in minutes. Share with your teams, or integrate in your platform. Drive growth in your business today! Designing great graphs quick, like Klipfolio, but easier. Many datasource plugins
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          What are some alternatives to AtScale and Cumul.io?
          Denodo
          It is the leader in data virtualization providing data access, data governance and data delivery capabilities across the broadest range of enterprise, cloud, big data, and unstructured data sources without moving the data from their original repositories.
          Apache Impala
          Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
          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.
          Snowflake
          Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
          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.
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