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cowtowncoder/jackson-dataformat-spade

Analysis updated 2026-08-11 · repo last pushed 2016-12-07

JavaAudience · developerComplexity · 3/5DormantSetup · moderate

TLDR

Spade is an experimental data format that stores information by columns instead of rows, using small data chunks for fast, low-memory processing of data while it moves through a system.

Mindmap

mindmap
  root((repo))
    What it does
      Column-oriented data format
      Small kilobyte-sized chunks
      Low memory requirements
    Format variants
      Binary for efficiency
      Text for troubleshooting
      Convertible between both
    Use cases
      Data pipelines
      Streaming applications
      On-the-fly filtering
    Tech stack
      Java
      Jackson ecosystem
    Audience
      Data pipeline developers
      Streaming app builders

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What do people build with it?

USE CASE 1

Build a streaming data pipeline that filters and transforms records on the fly with low latency.

USE CASE 2

Process column-oriented data in memory-constrained environments without large storage files.

USE CASE 3

Troubleshoot data encoding issues using the text format, then switch to binary for production efficiency.

What is it built with?

JavaJackson

How does it compare?

cowtowncoder/jackson-dataformat-spade0verflowme/intech-solabhishek-kumar09/configurate
LanguageJavaJavaJava
Last pushed2016-12-072022-11-162020-09-30
MaintenanceDormantDormantDormant
Setup difficultymoderatehardeasy
Complexity3/51/52/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires familiarity with the Jackson library ecosystem and understanding of column-oriented data concepts.

License information is not specified in the README.

In plain English

Spade is an experimental data format that organizes information by columns rather than by rows. While most common data formats bundle all the fields of a single record together before moving on to the next, this project groups all the values from a single field together. The key benefit is speed: it is designed to let systems encode and decode data fast enough to use while data is actively moving through a system, rather than only when it is sitting still in long-term storage. Most existing column-oriented formats are built for massive storage files. This project takes a different approach by keeping its data chunks much smaller, in the kilobyte range rather than the tens of megabytes. This keeps the memory requirements low for the software doing the reading and writing, and it reduces the delay before a chunk of data can be processed. It also lets processing systems interact with the data as if it were standard rows or records, meaning the software does not need to be specially programmed to understand the underlying column structure. Another notable feature is that the format supports both text and binary versions. The binary version is for efficiency, but the text version exists to make troubleshooting easier and to work with platforms like JavaScript that struggle with raw binary data. Because the underlying structure is the same for both, systems can easily convert between them. Developers building data pipelines or streaming applications would use this when they need fast, lightweight data processing. For example, a team building a system to filter or transform data on the fly could use it to process information with lower latency and less memory overhead than traditional storage-focused formats require. The README notes that further technical details are available in the project's wiki.

Copy-paste prompts

Prompt 1
How do I use jackson-dataformat-spade to encode my Java objects into a column-oriented binary format instead of JSON?
Prompt 2
Set up a Jackson ObjectMapper with Spade format to read and write small column-oriented data chunks in a streaming Java application.
Prompt 3
Show me how to convert between Spade text and binary formats using the Jackson Spade dataformat library so I can debug in text mode and run in binary mode.
Prompt 4
Create a Java data pipeline using jackson-dataformat-spade that processes records with low memory overhead using small column-oriented chunks.

Frequently asked questions

What is jackson-dataformat-spade?

Spade is an experimental data format that stores information by columns instead of rows, using small data chunks for fast, low-memory processing of data while it moves through a system.

What language is jackson-dataformat-spade written in?

Mainly Java. The stack also includes Java, Jackson.

Is jackson-dataformat-spade actively maintained?

Dormant — no commits in 2+ years (last push 2016-12-07).

What license does jackson-dataformat-spade use?

License information is not specified in the README.

How hard is jackson-dataformat-spade to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is jackson-dataformat-spade for?

Mainly developer.

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