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BlueData VS Apache ORC

Compare BlueData VS Apache ORC and see what are their differences

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BlueData logo BlueData

BlueData's software platform makes it easier, faster and more cost-effective for organizations to deploy Big Data infrastructure on-premises.

Apache ORC logo Apache ORC

Apache ORC is a columnar storage for Hadoop workloads.
  • BlueData Landing page
    Landing page //
    2023-06-13
  • Apache ORC Landing page
    Landing page //
    2022-09-18

BlueData features and specs

No features have been listed yet.

Apache ORC features and specs

  • Efficient Compression
    ORC provides highly efficient compression, which reduces the storage footprint of data and enhances performance by decreasing I/O operations.
  • Columnar Storage
    The columnar storage format significantly improves read performance by allowing for selective access to necessary columns while ignoring others.
  • Predicate Pushdown
    ORC supports predicate pushdown, enabling the query engine to skip over non-relevant data, thus enhancing query performance.
  • Type Richness
    ORC supports complex types (like structs and maps), making it suitable for diverse data storage and query needs.
  • Schema Evolution
    It facilitates seamless schema evolution, allowing easier adjustments to the dataset over time without breaking existing queries.
  • Built-in Indexes
    Indexes such as bloom filters and min/max values are built-in, accelerating query processing by enabling quicker data lookup.

Possible disadvantages of Apache ORC

  • Complexity
    The intricacies of its features may introduce additional complexity in implementation and maintenance, potentially increasing the learning curve.
  • Write Performance
    While ORC is optimized for read-heavy workloads, its write performance can be less efficient compared to other formats like Parquet.
  • Compatibility
    ORC may not be as widely supported as other formats, limiting the choice of tools and environments that can leverage its full capabilities.
  • Compression Overhead
    The process of compressing and decompressing data can introduce a computational overhead, affecting performance in some scenarios.

BlueData videos

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HPE BlueData Software Demo | AI, Machine Learning and Data Science

More videos:

  • Review - Kumar Sreekanti, BlueData - #BigDataSV 2016 - #theCUBE

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 BlueData and Apache ORC)

BlueData

Apache ORC

Data Dashboard
71 71%
Data Dashboard
29% 29
Big Data
60 60%
Big Data
40% 40
Data Management
67 67%
Data Management
33% 33
Databases
0 0%
Databases
100% 100

User comments

Share your experience with using BlueData 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.

BlueData mentions (0)

We have not tracked any mentions of BlueData yet. Tracking of BlueData 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 / almost 3 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 / almost 4 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 / about 4 years ago

What are some alternatives?

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

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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

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

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.

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

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