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Apache ORC VS Apache Kudu

Compare Apache ORC VS Apache Kudu and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache ORC logo Apache ORC

Apache ORC is a columnar storage for Hadoop workloads.

Apache Kudu logo Apache Kudu

Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.
  • Apache ORC Landing page
    Landing page //
    2022-09-18
  • Apache Kudu Landing page
    Landing page //
    2021-09-26

Apache ORC 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.

Apache ORC videos

No Apache ORC videos yet. You could help us improve this page by suggesting one.

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Apache Kudu videos

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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 Apache ORC and Apache Kudu)

Apache ORC

Apache Kudu

Big Data
100 100%
Big Data
0% 0
Office & Productivity
0 0%
Office & Productivity
100% 100
Data Dashboard
47 47%
Data Dashboard
53% 53
Technical Computing
0 0%
Technical Computing
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache ORC seems to be more popular. It has been mentiond 3 times since March 2021. 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.

Apache ORC mentions (3)

  • Java Serialization with Protocol Buffers
    The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 2 years ago
  • AWS EMR Cost Optimization Guide
    Data formatting is another place to make gains. When dealing with huge amounts of data, finding the data you need can take up a significant amount of your compute time. Apache Parquet and Apache ORC are columnar data formats optimized for analytics that pre-aggregate metadata about columns. If your EMR queries column intensive data like sum, max, or count, you can see significant speed improvements by reformatting... - Source: dev.to / over 3 years ago
  • Apache Hudi - The Streaming Data Lake Platform
    The following stack captures layers of software components that make up Hudi, with each layer depending on and drawing strength from the layer below. Typically, data lake users write data out once using an open file format like Apache Parquet/ORC stored on top of extremely scalable cloud storage or distributed file systems. Hudi provides a self-managing data plane to ingest, transform and manage this data, in a... - Source: dev.to / almost 4 years ago

Apache Kudu mentions (0)

We have not tracked any mentions of Apache Kudu yet. Tracking of Apache Kudu recommendations started around Mar 2021.

What are some alternatives?

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

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

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

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.

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.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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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