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  5. Cube.js vs IBM Cognos Analytics

Cube.js vs IBM Cognos Analytics

OverviewComparisonAlternatives

Overview

Cube
Cube
Stacks96
Followers258
Votes30
IBM Cognos Analytics
IBM Cognos Analytics
Stacks19
Followers17
Votes0

Cube.js vs IBM Cognos Analytics: What are the differences?

  1. Data Modeling: Cube.js focuses on building complex analytical web applications by providing a powerful semantic layer for data modeling through its schema markup language. In contrast, IBM Cognos Analytics offers data modeling capabilities but primarily focuses on providing pre-built data models and integration with various data sources, making it more suitable for users requiring less flexible modeling capabilities.

  2. Self-Service Analytics: Cube.js is designed for developers to create customizable, self-service analytics applications for end-users through its API-centric approach. On the other hand, IBM Cognos Analytics caters more towards business users by offering a user-friendly, drag-and-drop interface for creating reports and dashboards without the need for extensive coding skills.

  3. Open Source vs. Enterprise Solution: Cube.js is an open-source platform, allowing developers to freely access and modify its codebase to suit their specific needs. In contrast, IBM Cognos Analytics is an enterprise solution that comes with a licensing fee, offering extensive support, security features, and integrations with other IBM products for businesses requiring a comprehensive analytics solution.

  4. Real-Time vs. Batch Processing: Cube.js emphasizes real-time data processing, enabling developers to build applications that provide up-to-date insights for users. IBM Cognos Analytics, while offering real-time data connectivity capabilities, is more commonly used for batch processing of data for scheduled reporting and analysis, making it better suited for businesses that do not require constant real-time updates.

  5. Scalability and Performance: Cube.js is known for its scalable architecture, allowing developers to handle large datasets and high user loads efficiently through its use of pre-aggregated data and optimized query execution. IBM Cognos Analytics also provides scalability features but may require additional configurations and resources to achieve optimal performance for handling complex analytics tasks at scale.

  6. Integration and Ecosystem: Cube.js is designed to integrate seamlessly with various data sources and front-end frameworks, offering a flexible ecosystem for developers to work with. IBM Cognos Analytics, on the other hand, provides robust integrations with IBM's cloud services and business intelligence tools, making it a preferred choice for organizations already using IBM solutions for their analytics needs.

In Summary, Cube.js and IBM Cognos Analytics differ in their approach to data modeling, target audience, pricing model, processing capabilities, scalability, and ecosystem integrations.

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Detailed Comparison

Cube
Cube
IBM Cognos Analytics
IBM Cognos Analytics

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

It is a business intelligence solution that empowers users with AI-infused self-service capabilities that accelerate data preparation, analysis, and report creation. It makes it easier than ever to visualize data and share actionable insights across your organization to foster more data-driven decisions.

* Pre-aggregation; * Caching; * Data modeling; * APIs; * Works with any relational database;
Protect your data; Visualize your business performance; Share critical insights easily
Statistics
Stacks
96
Stacks
19
Followers
258
Followers
17
Votes
30
Votes
0
Pros & Cons
Pros
  • 8
    API
  • 6
    Open Source
  • 6
    Caching
  • 6
    Visualization agnostic
  • 4
    Rollups orchestration
Cons
  • 1
    No ability to update "cubes" in runtime
  • 1
    Poor performance
  • 1
    Doesn't support filtering on left joins
  • 1
    Incomplete documentation
  • 1
    Cannot use as a lib - only HTTP
No community feedback yet
Integrations
Amazon Redshift
Amazon Redshift
Google BigQuery
Google BigQuery
Microsoft SQL Server
Microsoft SQL Server
Snowflake
Snowflake
Presto
Presto
MySQL
MySQL
PostgreSQL
PostgreSQL
Microsoft Azure
Microsoft Azure
Oracle
Oracle
Amazon Athena
Amazon Athena
No integrations available

What are some alternatives to Cube, IBM Cognos Analytics?

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.

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.

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.

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.

Redash

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

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.

Periscope

Periscope

Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

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