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Impala VS Apache Kudu

Compare Impala VS Apache Kudu and see what are their differences

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Impala logo Impala

Impala is a modern, open source, distributed SQL query engine for Apache Hadoop.

Apache Kudu logo Apache Kudu

Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.
  • Impala Landing page
    Landing page //
    2023-04-02
  • Apache Kudu Landing page
    Landing page //
    2021-09-26

Impala features and specs

No features have been listed yet.

Apache Kudu features and specs

  • Fast Analytics on Fresh Data
    Kudu is designed for fast analytical processing on up-to-date data. It allows for efficient columnar storage which enables quick read and write capabilities suitable for real-time analytics.
  • Hybrid Workloads
    Supports hybrid workloads of both analytical and transactional processing, making it versatile for use cases that require both types of operations.
  • Seamless Integration
    Integrates well with the Apache ecosystem, particularly with Apache Hadoop, Apache Impala, and Apache Spark, enabling a cohesive environment for data processing and management.
  • Fine-grained Updates
    Allows for efficient updates to individual columns and rows, which is useful for applications that require frequent updates alongside analytic capabilities.
  • Schema Evolution
    Supports schema evolution, which allows for adding, dropping, and renaming columns without costly table rewrites.

Possible disadvantages of Apache Kudu

  • Complexity in Installation and Configuration
    The setup and configuration of Kudu can be complex, requiring a good understanding of its architecture and dependencies.
  • Limited SQL Support
    While Kudu is optimized for analytical tasks, its SQL capabilities are limited compared to some traditional RDBMS systems, which might require additional tools for more complex queries.
  • Community and Ecosystem
    Although growing, the community and ecosystem around Kudu are smaller compared to more established systems, which may result in less available resources and third-party tools.
  • Memory Intensive
    Kudu can be memory-intensive, which might require more hardware resources compared to other systems, especially as data volumes grow.
  • Write Performance Limitations
    While Kudu offers fast reads, its write performance can be slower compared to systems specifically optimized for high-speed transactional processing.

Impala videos

+ Add

2016 Chevrolet Impala - Review and Road Test

More videos:

  • Review - 2020 Chevrolet Impala Review | The Final Year
  • Review - Is it the END of the road for the 2019 Chevy Impala?

Apache Kudu videos

+ Add

Apache Kudu and Spark SQL for Fast Analytics on Fast Data (Mike Percy)

More videos:

  • Review - Apache Kudu (Incubating): New Hadoop Storage for Fast Analytics on Fast Data
  • Review - Apache Kudu: Fast Analytics on Fast Data | DataEngConf SF '16

Category Popularity

0-100% (relative to Impala and Apache Kudu)

Impala

Apache Kudu

Data Dashboard
46 46%
Data Dashboard
54% 54
Office & Productivity
0 0%
Office & Productivity
100% 100
Data Management
100 100%
Data Management
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

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What are some alternatives?

When comparing Impala and Apache Kudu, you can also consider the following products

SQream - SQream empowers organizations to analyze the full scope of their Massive Data, from terabytes to petabytes, to achieve critical insights which were previously unattainable.

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

Apache ORC - Apache ORC is a columnar storage for Hadoop workloads.

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

Delta Lake - Application and Data, Data Stores, and Big Data Tools

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

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