Software Alternatives & Reviews

Impala VS Apache Parquet

Compare Impala VS Apache Parquet and see what are their differences

Impala logo Impala

Impala is a modern, open source, distributed SQL query engine for Apache Hadoop.

Apache Parquet logo Apache Parquet

Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.
  • Impala Landing page
    Landing page //
    2023-04-02
  • Apache Parquet Landing page
    Landing page //
    2022-06-17

Impala

Categories
  • Big Data
  • Big Data Infrastructure
  • Databases
  • Data Dashboard
Website impala.apache.org
Details $

Apache Parquet

Categories
  • Databases
  • Big Data
  • Relational Databases
  • NoSQL Databases
Website parquet.apache.org
Details $

Impala videos

2016 Chevrolet Impala - Review and Road Test

More videos:

  • Review - 2020 Chevrolet Impala Review | The Final Year
  • Review - Is it the END of the road for the 2019 Chevy Impala?

Apache Parquet videos

No Apache Parquet videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Impala and Apache Parquet)
Big Data
34 34%
66% 66
Databases
24 24%
76% 76
Data Dashboard
62 62%
38% 38
NoSQL Databases
0 0%
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 19 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.

Impala mentions (0)

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

Apache Parquet mentions (19)

  • [D] Is there other better data format for LLM to generate structured data?
    The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 4 months ago
  • Demystifying Apache Arrow
    Apache Parquet (Parquet for short), which nowadays is an industry standard to store columnar data on disk. It compress the data with high efficiency and provides fast read and write speeds. As written in the Arrow documentation, "Arrow is an ideal in-memory transport layer for data that is being read or written with Parquet files". - Source: dev.to / 11 months ago
  • Parquet: more than just "Turbo CSV"
    Googling that suggests this page: https://parquet.apache.org/. Source: 12 months ago
  • Beginner question about transformation
    You should also consider distribution of data because in a company that has machine learning workflows, the same data may need to go through different workflows using different technologies and stored in something other than a data warehouse, e.g. Feature engineering in Spark and loaded/stored in binary format such as Parquet in a data lake/object store. Source: about 1 year ago
  • Pandas Free Online Tutorial In Python — Learn Pandas Basics In 5 Lessons!
    This section will teach you how to read and write data to and from a variety of file types, including CSV, Excel, SQL, HTML, Parquet, JSON etc. You’ll also learn how to manipulate data from other sources, such as databases and web sites. Source: about 1 year ago
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What are some alternatives?

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

Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Apache ORC - Apache ORC is a columnar storage for Hadoop workloads.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

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

Fujitsu Symfoware Analytics Server - Fujitsu Symfoware Analytics Server is a high-performance database software that is designed for use with data warehouses.