Amazon Redshift Spectrum vs Apache Flink

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Amazon Redshift Spectrum
Amazon Redshift Spectrum

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Apache Flink

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Amazon Redshift Spectrum vs Apache Flink: What are the differences?

Developers describe Amazon Redshift Spectrum as "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. On the other hand, Apache Flink is detailed as "Fast and reliable large-scale data processing engine". 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.

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

Apache Flink is an open source tool with 9.35K GitHub stars and 5K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

According to the StackShare community, Apache Flink has a broader approval, being mentioned in 20 company stacks & 22 developers stacks; compared to Amazon Redshift Spectrum, which is listed in 5 company stacks and 4 developer stacks.

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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 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.
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        What are some alternatives to Amazon Redshift Spectrum and Apache Flink?
        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.
        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.
        Apache Hive
        Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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        How developers use Amazon Redshift Spectrum and Apache Flink
        Avatar of Coolfront Technologies
        Coolfront Technologies uses Apache FlinkApache Flink

        Used for analytics on streaming data.

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        rmetzger uses Apache FlinkApache Flink

        Flink for stream data analytics

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