tape VS Apache Orc

Compare tape vs Apache Orc and see what are their differences.

tape

A lightning fast, transactional, file-based FIFO for Android and Java. (by square)

Apache Orc

Apache ORC - the smallest, fastest columnar storage for Hadoop workloads (by apache)
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tape Apache Orc
- 4
2,465 710
- 1.0%
0.0 9.4
almost 2 years ago 5 days ago
Java Java
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

tape

Posts with mentions or reviews of tape. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning tape yet.
Tracking mentions began in Dec 2020.

Apache Orc

Posts with mentions or reviews of Apache Orc. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-01.
  • Java Serialization with Protocol Buffers
    6 projects | dev.to | 1 Nov 2022
    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.
  • Personal data of 120,000 Russian servicemen fighting in Ukraine made public
    2 projects | /r/worldnews | 1 Mar 2022
  • AWS EMR Cost Optimization Guide
    1 project | dev.to | 14 Dec 2021
    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 data like CSVs into one of these columnar formats.
  • Apache Hudi - The Streaming Data Lake Platform
    8 projects | dev.to | 27 Jul 2021
    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 way that unlocks incremental data processing on them.

What are some alternatives?

When comparing tape and Apache Orc you can also consider the following projects:

Big Queue - A big, fast and persistent queue based on memory mapped file.

Apache Thrift - Apache Thrift

Persistent Collection - A Persistent Java Collections Library

Apache Avro - Apache Avro is a data serialization system.

Wire - gRPC and protocol buffers for Android, Kotlin, Swift and Java.

Apache Parquet - Apache Parquet Java

Androl4b - A Virtual Machine For Assessing Android applications, Reverse Engineering and Malware Analysis

Protobuf - Protocol Buffers - Google's data interchange format

AutobahnAndroid - WebSocket & WAMP in Java for Android and Java 8

iceberg - Apache Iceberg

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Nutrient - The #1 PDF SDK Library
Bad PDFs = bad UX. Slow load times, broken annotations, clunky UX frustrates users. Nutrient’s PDF SDKs gives seamless document experiences, fast rendering, annotations, real-time collaboration, 100+ features. Used by 10K+ devs, serving ~half a billion users worldwide. Explore the SDK for free.
nutrient.io
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