tape VS Apache Orc

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


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
0 2
2,406 484
0.0% 4.3%
0.0 9.4
about 1 year ago 3 days ago
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.


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 2021-07-27.
  • 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 Parquet - Apache Parquet

Apache Avro - Apache Avro is a data serialization system.

debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.

Protobuf - Protocol Buffers - Google's data interchange format

Persistent Collection - A Persistent Java Collections Library

Apache Thrift - Apache Thrift

SBE - Simple Binary Encoding (SBE) - High Performance Message Codec

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

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

StatusBarUtil - A util for setting status bar style on Android App.