Software Alternatives & Reviews

RJ Metrics VS Apache Parquet

Compare RJ Metrics VS Apache Parquet and see what are their differences

RJ Metrics logo RJ Metrics

RJMetrics provides hosted business intelligence & data analysis software to companies that operate online.

Apache Parquet logo Apache Parquet

Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.
  • RJ Metrics Landing page
    Landing page //
    2023-07-06
  • Apache Parquet Landing page
    Landing page //
    2022-06-17

RJ Metrics videos

RJ Metrics

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  • Review - Props RJ Metrics Promo

Apache Parquet videos

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Category Popularity

0-100% (relative to RJ Metrics and Apache Parquet)
eCommerce
100 100%
0% 0
Databases
0 0%
100% 100
Analytics
100 100%
0% 0
Big Data
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.

RJ Metrics mentions (0)

We have not tracked any mentions of RJ Metrics yet. Tracking of RJ Metrics 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: 5 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: about 1 year 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 RJ Metrics and Apache Parquet, you can also consider the following products

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

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

CAKE - CAKE provides a SaaS-based solution for advertisers, publishers and networks to track, attribute and optimize their spend in real-time.

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

Woopra - Track your customers' web and mobile activity, forms, emails, support tickets and more, all in one place with customer analytics. Analyze and take action.

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