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Qubole VS Apache ORC

Compare Qubole VS Apache ORC and see what are their differences

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Qubole logo Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Apache ORC logo Apache ORC

Apache ORC is a columnar storage for Hadoop workloads.
  • Qubole Landing page
    Landing page //
    2023-06-22
  • Apache ORC Landing page
    Landing page //
    2022-09-18

Qubole videos

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Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos:

  • Review - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • Review - Democratizing Data with Qubole

Apache ORC videos

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

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Category Popularity

0-100% (relative to Qubole and Apache ORC)

Qubole

Apache ORC

Data Dashboard
89 89%
Data Dashboard
11% 11
Databases
0 0%
Databases
100% 100
Big Data
78 78%
Big Data
22% 22
Data Warehousing
100 100%
Data Warehousing
0% 0

User comments

Share your experience with using Qubole and Apache ORC. For example, how are they different and which one is better?
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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.

Qubole mentions (0)

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

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 1 year 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 2 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 3 years ago

What are some alternatives?

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

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

Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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

Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

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