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Based on our record, Apache Hive seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on Reddit, HackerNews and some other platforms. They can help you identify which product is more popular and what people think of it.
Both Fortune 500 and small companies are looking for competent people who can derive useful insight from their huge pile of data and that's where Big Data Framework like Apache Hadoop, Apache Spark, Flink, Storm, and Hive can help. - Source: dev.to / 5 months ago
How to flesh this idea out more? Start ingesting different types of events and putting them in different tables. Definitely try an OLAP solution (Hive? Most of my experience sits with closed source projects that only a company can afford) and think about column optimised file formats. Get the raw data into an OLAP solution and do aggregations into another systems based off of the OLAP solution. - Source: Reddit / 3 months ago
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Apache Kylin - OLAP Engine for Big Data