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Owler VS Apache Kylin

Compare Owler VS Apache Kylin and see what are their differences

Grapple
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Owler logo Owler

Owler is a crowdsourced data model allowing users to follow, track, and research companies.

Apache Kylin logo Apache Kylin

OLAP Engine for Big Data
  • Owler Landing page
    Landing page //
    2023-10-18
  • Apache Kylin Landing page
    Landing page //
    2023-06-29

Owler features and specs

  • Competitive Insights
    Owler provides detailed competitive insights, including news, financials, and key personnel changes, enabling businesses to stay informed about their competitors.
  • User-Generated Data
    The platform leverages crowdsourced data, which can offer unique perspectives and more frequent updates on company information compared to official records.
  • Customizable Alerts
    Users can set up customizable alerts for specific companies or industries, ensuring they receive timely updates relevant to their interests.
  • Free Basic Plan
    Owler offers a basic plan at no cost, which is beneficial for startups and small businesses with limited budgets.
  • Community Interaction
    The platform encourages user interaction to rate and review companies, which can provide a more community-driven assessment of businesses.

Possible disadvantages of Owler

  • Data Accuracy
    Since much of Owler's data is user-generated, there may be concerns about the accuracy and reliability of the information provided.
  • Limited Features in Free Plan
    The free plan has limited functionalities and access to deeper insights often requires a paid subscription.
  • User Interface
    Some users find the interface to be less intuitive and in need of improvements for better navigation and user experience.
  • Data Coverage
    Owler may not cover all companies or industries comprehensively, potentially leaving gaps in competitive analysis.
  • Dependence on Community Activity
    The quality and quantity of data can heavily depend on how active the user community is, which might lead to inconsistent information across different sectors.

Apache Kylin features and specs

  • High Query Performance
    Apache Kylin is designed for high-performance, low-latency analytics on large datasets. Its OLAP engine pre-computes and stores aggregated queries, which speeds up query responses significantly.
  • Scalability
    Kylin can handle massive volumes of data, making it suitable for large scale data warehousing needs. It is designed to scale out by distributing the workload across a cluster of servers.
  • Integration with Hadoop Ecosystem
    Kylin integrates seamlessly with the Hadoop ecosystem, leveraging tools like Hive, HBase, and Spark to facilitate data processing and storage, thereby enhancing its functionality and compatibility.
  • Support for Multi-dimensional Analysis
    It provides strong multidimensional analysis capabilities, allowing for complex queries using well-known BI tools like Tableau and Power BI.

Possible disadvantages of Apache Kylin

  • Complex Setup
    Setting up and configuring Apache Kylin can be complex and time-consuming, requiring a deep understanding of the Hadoop ecosystem and its components.
  • Resource Intensity
    The pre-computation of data cubes and their storage can be resource-intensive, consuming significant memory and storage capacity.
  • Limited Flexibility in Querying
    Pre-aggregated cube-based analysis may not cover all ad-hoc queries. Kylin's strength lies in pre-aggregated queries but may fall short in handling highly dynamic, on-the-fly queries.
  • Maintenance Overhead
    Maintaining Kylinโ€™s precomputed cubes can become cumbersome, particularly as data evolves or changes frequently, requiring updates or recalculations of cubes.

Analysis of Owler

Overall verdict

  • Overall, Owler is considered a good tool for individuals and businesses seeking to enhance their competitive intelligence capabilities. It offers a wide array of features that make it a valuable resource for staying informed about industry movements and competitor actions.

Why this product is good

  • Owler is a business information and crowdsourced competitive intelligence platform that provides company data, news updates, and industry analysis. It is useful for gaining insights into competitors, tracking market trends, and obtaining company profiles. Users appreciate it for offering data that is continuously updated and verified by a community of contributors.

Recommended for

    Owler is particularly recommended for business analysts, sales and marketing professionals, and entrepreneurs who need reliable and up-to-date information on competitors and market trends. It's also beneficial for investors and job seekers looking to research companies.

Owler videos

+ Add

Owler Introduction

More videos:

  • Review - Owler Ashford Marathon, Half Marathon and 10k 2017. Grit and Ice were the themes here...

Apache Kylin videos

+ Add

Extreme OLAP Analytics with Apache Kylin - Big Data Application Meetup

More videos:

  • Review - Apache Kylin: OLAP Cubes for NoSQL Data stores
  • Review - Installing Apache Kylin in Cloudera Quickstart VM Sandbox

Category Popularity

0-100% (relative to Owler and Apache Kylin)

Owler

Apache Kylin

Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
0 0%
Databases
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0
Data Management
0 0%
Data Management
100% 100

User comments

Share your experience with using Owler and Apache Kylin. For example, how are they different and which one is better?
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Social recommendations and mentions

Apache Kylin might be a bit more popular than Owler. We know about 1 link to it since March 2021 and only 1 link to Owler. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Owler mentions (1)

  • A web app/executable that can collect data from a number of databases.
    Owler is a good example of the type of app I need: https://corp.owler.com/. Source: over 4 years ago

Apache Kylin mentions (1)

  • Apache Kafka Use Cases: When To Use It & When Not To
    A Kafka-based data integration platform will be a good fit here. The services can add events to different topics in a broker whenever there is a data update. Kafka consumers corresponding to each of the services can monitor these topics and make updates to the data in real-time. It is also possible to create a unified data store through the same integration platform. Developers can implement a unified store either... - Source: dev.to / almost 4 years ago

What are some alternatives?

When comparing Owler and Apache Kylin, you can also consider the following products

QlikSense - A business discovery platform that delivers self-service business intelligence capabilities

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Whatagraph - Whatagraph is the most visual multi-source marketing reporting platform. Built in collaboration with digital marketing agencies

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

Foxmetrics - We track the interactions of your customers with your web or mobile applications in real-time, and provide actionable metrics that will help increase your conversion.

Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.

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