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  5. Denodo vs Kyvos

Denodo vs Kyvos

OverviewComparisonAlternatives

Overview

Denodo
Denodo
Stacks40
Followers120
Votes0
GitHub Stars0
Forks0
Kyvos
Kyvos
Stacks13
Followers32
Votes0

Denodo vs Kyvos: What are the differences?

Denodo: Data virtualisation platform, allowing you to connect disparate data from any source. 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; Kyvos: BI acceleration platform for the cloud and on-premise data lakes. It is the world’s most powerful BI acceleration platform that delivers instant insights at petabyte scale, both on the cloud and on-premise data lakes. Our breakthrough OLAP technology revolutionizes analytics by enabling users to visualize, explore, and analyze massive volumes of data with sub-second response times.

Denodo and Kyvos can be categorized as "Business Intelligence" tools.

Some of the features offered by Denodo are:

  • Data virtualization
  • Data query
  • Data views

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

  • Semantic layer powered by next-generation OLAP
  • Instant responses at massive scale
  • Scale-out architecture for concurrent access

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Detailed Comparison

Denodo
Denodo
Kyvos
Kyvos

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.

Kyvos is a BI acceleration platform that helps users analyze big data on the cloud with exceptionally high performance using any BI tool they like. You can accelerate your cloud analytics while optimizing your costs with Kyvos.

Data virtualization; Data query; Data views
Accelerate BI - Instant insights on trillions of rows; OLAP Modernization - Cloud-native Smart OLAP built to scale; Reduce Cloud Costs - Build-once-query-multiple-times approach for cost-effective BI; No Data Engineering - Simplified UI-based data modelling; Universal semantic layer - One version of truth across the business; Support for all cloud platforms and BI tools; Enterprise security features with row and column level security
Statistics
GitHub Stars
0
GitHub Stars
-
GitHub Forks
0
GitHub Forks
-
Stacks
40
Stacks
13
Followers
120
Followers
32
Votes
0
Votes
0
Integrations
DataRobot
DataRobot
AtScale
AtScale
Vertica
Vertica
Trifacta
Trifacta
Dremio
Dremio
Apache Kylin
Apache Kylin
SAP HANA
SAP HANA
Snowflake
Snowflake
Amazon S3
Amazon S3
PostgreSQL
PostgreSQL
Cloudera Enterprise
Cloudera Enterprise
R Language
R Language
Tableau
Tableau
Python
Python
AWS Glue
AWS Glue
Microsoft Azure
Microsoft Azure
Google Cloud Platform
Google Cloud Platform

What are some alternatives to Denodo, Kyvos?

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.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

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.

NumPy

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

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.

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