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Apache Parquet VS Infinispan

Compare Apache Parquet VS Infinispan and see what are their differences

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Apache Parquet logo Apache Parquet

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

Infinispan logo Infinispan

A distributed in-memory key/value data store with optional schema.
  • Apache Parquet Landing page
    Landing page //
    2022-06-17
  • Infinispan Landing page
    Landing page //
    2023-10-04

Apache Parquet features and specs

  • Columnar Storage
    Apache Parquet uses columnar storage, which allows for efficient retrieval of only the data you need, reducing I/O and improving query performance on large datasets.
  • Compression
    Parquet files support efficient compression and encoding schemes, resulting in significant storage savings and less data to transfer over the network.
  • Compatibility
    It is compatible with the Hadoop ecosystem, including tools like Apache Spark, Hive, and Impala, making it versatile for big data processing.
  • Schema Evolution
    Parquet supports schema evolution, allowing changes to the schema without breaking existing data, which helps in maintaining long-lived data pipelines.
  • Efficient Read Performance for Aggregations
    Due to its columnar layout, Parquet is highly efficient for processing queries that aggregate data across columns, such as SUM and AVERAGE.

Possible disadvantages of Apache Parquet

  • Write Performance
    Writing data to Parquet can be slower compared to row-based formats, particularly for small inserts or updates, due to the overhead of encoding and compression.
  • Complexity in File Management
    Managing and partitioning Parquet files to optimize performance can become complex, particularly as datasets grow in size and complexity.
  • Not Ideal for All Workloads
    Workloads that require frequent row-level updates or involve small queries might be less efficient with Parquet due to its columnar nature.
  • Learning Curve
    The need to understand the nuances of columnar storage, encoding, and compression can pose a learning curve for teams new to Parquet.

Infinispan features and specs

No features have been listed yet.

Apache Parquet videos

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Infinispan videos

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Infinispan admin console - concepts overview

More videos:

  • Review - Infinispan 9.1 admin console - What's new
  • Review - Infinispan from POC to Production

Category Popularity

0-100% (relative to Apache Parquet and Infinispan)

Apache Parquet

Infinispan

Databases
72 72%
Databases
28% 28
Big Data
100 100%
Big Data
0% 0
NoSQL Databases
36 36%
NoSQL Databases
64% 64
Data Management
100 100%
Data Management
0% 0

User comments

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Social recommendations and mentions

Based on our record, Apache Parquet seems to be a lot more popular than Infinispan. While we know about 25 links to Apache Parquet, we've tracked only 1 mention of Infinispan. 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.

Apache Parquet mentions (25)

  • 🔥 Simulating Course Schedules 600x Faster with Web Workers in CourseCast
    If there was a way to package and compress the Excel spreadsheet in a web-friendly format, then there's nothing stopping us from loading the entire dataset in the browser!1 Sure enough, the Parquet file format was specifically designed for efficient portability. - Source: dev.to / about 1 month ago
  • How to Pitch Your Boss to Adopt Apache Iceberg?
    Iceberg decouples storage from compute. That means your data isn’t trapped inside one proprietary system. Instead, it lives in open file formats (like Apache Parquet) and is managed by an open, vendor-neutral metadata layer (Apache Iceberg). - Source: dev.to / 6 months ago
  • Processing data with “Data Prep Kit” (part 2)
    Data prep kit github repository: https://github.com/data-prep-kit/data-prep-kit?tab=readme-ov-file Quick start guide: https://github.com/data-prep-kit/data-prep-kit/blob/dev/doc/quick-start/contribute-your-own-transform.md Provided samples and examples: https://github.com/data-prep-kit/data-prep-kit/tree/dev/examples Parquet: https://parquet.apache.org/. - Source: dev.to / 6 months ago
  • 🔬Public docker images Trivy scans as duckdb datas on Kaggle
    Deliver nice ready-to-use data as duckdb, parquet and csv. - Source: dev.to / 6 months ago
  • Introducing Promptwright: Synthetic Dataset Generation with Local LLMs
    Push the dataset to hugging face in parquet format. - Source: dev.to / 11 months ago
View more

Infinispan mentions (1)

  • Created a simple key value pair cache in Golang using a custom tcp protocol(for fun, don't use this in production usage)
    You can already download it for free you know. Source: over 2 years ago

What are some alternatives?

When comparing Apache Parquet and Infinispan, you can also consider the following products

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

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

memcached - High-performance, distributed memory object caching system

DuckDB - DuckDB is an in-process SQL OLAP database management system

CouchBase - Document-Oriented NoSQL Database

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