Amazon Redshift Spectrum vs Pachyderm

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Amazon Redshift Spectrum
Amazon Redshift Spectrum

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Pachyderm
Pachyderm

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Amazon Redshift Spectrum vs Pachyderm: What are the differences?

Amazon Redshift Spectrum: Exabyte-Scale In-Place Queries of S3 Data. With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data; Pachyderm: MapReduce without Hadoop. Analyze massive datasets with Docker. Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.

Amazon Redshift Spectrum and Pachyderm can be primarily classified as "Big Data" tools.

Pachyderm is an open source tool with 3.81K GitHub stars and 369 GitHub forks. Here's a link to Pachyderm's open source repository on GitHub.

- No public GitHub repository available -

What is Amazon Redshift Spectrum?

With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.

What is Pachyderm?

Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.
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        What tools integrate with Amazon Redshift Spectrum?
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        What are some alternatives to Amazon Redshift Spectrum and Pachyderm?
        Amazon Athena
        Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
        Amazon Redshift
        It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
        Apache Spark
        Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
        Apache Flink
        Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
        Presto
        Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
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