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Apache Parquet VS Admin4

Compare Apache Parquet VS Admin4 and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Reviews
  3. ยป Alternatives

Apache Parquet logo Apache Parquet

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

Admin4 logo Admin4

Admin4 is a tool for server maintenance via several plugin modules, running on Windows, Mac OSX, Linux and many more platforms. Currently, plugins for BIND DNS, LDAP, IMAP and PostgreSQL are included.
  • Apache Parquet Landing page
    Landing page //
    2022-06-17
  • Admin4 Landing page
    Landing page //
    2020-05-02

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.

Admin4 features and specs

  • Multi-Domain Support
    Admin4 offers the capability to manage multiple domains from a single interface, which is beneficial for administrators handling complex server environments.
  • Cross-Platform Compatibility
    The tool is available on various operating systems, including Windows, macOS, and Linux, allowing administrators flexibility in their choice of server environment.
  • Graphical Interface
    Admin4 provides a user-friendly graphical interface, making it more accessible for users who may not be comfortable with command-line tools.
  • Open Source
    Being open-source, Admin4 allows users to contribute to its development and customize it to better fit their specific needs.

Possible disadvantages of Admin4

  • Limited Feature Set
    Compared to some commercial alternatives, Admin4 might have a less comprehensive feature set, potentially lacking certain advanced features some administrators may need.
  • Community Support
    As an open-source project, it may rely heavily on community support, which can result in slower response times for addressing issues or bugs.
  • Less Frequent Updates
    Open-source tools like Admin4 may not receive updates as frequently as some proprietary tools, which could impact security and the addition of new features.
  • Learning Curve
    Although its graphical interface is user-friendly, some users might still face a learning curve, especially if they are transitioning from a different system administration tool.

Analysis of Admin4

Overall verdict

  • Admin4 is a decent choice for simple, budget-conscious domain registration and basic hosting needs, though it lacks the advanced features and extensive support infrastructure of larger, more established providers.

Why this product is good

  • Offers competitively priced domain registration and renewal rates
  • Simple, no-frills interface that is easy for beginners to navigate
  • Provides basic domain management tools including DNS management
  • Includes essential features like WHOIS privacy protection on many plans
  • Straightforward checkout process without excessive upselling

Recommended for

  • Individuals registering a single domain for personal use
  • Small budget-conscious website owners
  • Users who need basic domain management without complex features
  • Hobbyist webmasters running simple personal or small business sites
  • Customers prioritizing low cost over advanced customer support

Category Popularity

0-100% (relative to Apache Parquet and Admin4)

Apache Parquet

Admin4

Databases
100 100%
Databases
0% 0
Control Panels
0 0%
Control Panels
100% 100
Big Data
100 100%
Big Data
0% 0
System Administration
0 0%
System Administration
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Parquet seems to be more popular. It has been mentiond 31 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.

Apache Parquet mentions (31)

  • Can you build observability ingestion on S3 alone โ€” no Kafka, no disks, no coordination layer?
    Apache Iceberg fits these requirements well. Iceberg stores data as immutable Apache Parquet files and adds them through atomic commits, so readers always see a consistent snapshot. A separate metadata layer prunes files by their statistics before the data itself is ever read, and those statistics can be extended to match an observability filtering profile. - Source: dev.to / about 1 month ago
  • Zeroserve: A zero-config web server you can script with eBPF
    Depends on the domain. There's a bunch of sciences using large datasets served up efficiently using static file formats, e.g., https://zarr.dev/ and https://parquet.apache.org/. - Source: Hacker News / about 2 months ago
  • What Are Table Formats and Why Were They Needed?
    The data files themselves are still standard Parquet or ORC. The table format adds a metadata layer on top that gives those files the properties of a database table. - Source: dev.to / 3 months ago
  • So, you know what? I just wasted 3 months of my life
    The dataset is huge - in parquet conversion - it is total 9gb. And in raw PNG image nested folders - it is 67 gigabytes. Huge... - Source: dev.to / 5 months ago
  • Fix Slow Query: A Developer's Guide to Data Warehouse Performance
    The solution is to standardize on columnar formats like Apache Parquet. Parquet stores data in columns, not rows, which immediately enables column pruning. If a query is SELECT avg(price) FROM sales, the engine reads only the price column and ignores all others. This can reduce storage footprints by up to 75% compared to raw formats and is a cornerstone of modern analytics performance. - Source: dev.to / 9 months ago
View more

Admin4 mentions (0)

We have not tracked any mentions of Admin4 yet. Tracking of Admin4 recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Parquet and Admin4, you can also consider the following products

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

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

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

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

Apache Avro - Apache Avro is a comprehensive data serialization system and acting as a source of data exchanger service for Apache Hadoop.

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

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