Amazon Redshift vs Amazon Redshift Spectrum

Amazon Redshift
Amazon Redshift

596
294
+ 1
86
Amazon Redshift Spectrum
Amazon Redshift Spectrum

32
31
+ 1
0
Add tool

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

Developers describe Amazon Redshift as "Fast, fully managed, petabyte-scale data warehouse service". Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets 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. On the other hand, Amazon Redshift Spectrum is detailed 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.

Amazon Redshift can be classified as a tool in the "Big Data as a Service" category, while Amazon Redshift Spectrum is grouped under "Big Data Tools".

Lyft, Coursera, and 9GAG are some of the popular companies that use Amazon Redshift, whereas Amazon Redshift Spectrum is used by VSCO, CommonBond, and intermix.io. Amazon Redshift has a broader approval, being mentioned in 270 company stacks & 68 developers stacks; compared to Amazon Redshift Spectrum, which is listed in 5 company stacks and 4 developer stacks.

- No public GitHub repository available -
- No public GitHub repository available -

What is Amazon Redshift?

Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets 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.

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.

Want advice about which of these to choose?Ask the StackShare community!

Why do developers choose Amazon Redshift?
Why do developers choose Amazon Redshift Spectrum?
    Be the first to leave a pro

    Sign up to add, upvote and see more prosMake informed product decisions

    What are the cons of using Amazon Redshift?
    What are the cons of using Amazon Redshift Spectrum?
      Be the first to leave a con
        Be the first to leave a con
        What companies use Amazon Redshift?
        What companies use Amazon Redshift Spectrum?

        Sign up to get full access to all the companiesMake informed product decisions

        What tools integrate with Amazon Redshift?
        What tools integrate with Amazon Redshift Spectrum?

        Sign up to get full access to all the tool integrationsMake informed product decisions

        What are some alternatives to Amazon Redshift and Amazon Redshift Spectrum?
        Google BigQuery
        Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
        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 DynamoDB
        All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
        Hadoop
        The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
        Amazon EMR
        Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year.
        See all alternatives
        Decisions about Amazon Redshift and Amazon Redshift Spectrum
        No stack decisions found
        Interest over time
        Reviews of Amazon Redshift and Amazon Redshift Spectrum
        No reviews found
        How developers use Amazon Redshift and Amazon Redshift Spectrum
        Avatar of Olo
        Olo uses Amazon RedshiftAmazon Redshift

        Aggressive archiving of historical data to keep the production database as small as possible. Using our in-house soon-to-be-open-sourced ETL library, SharpShifter.

        Avatar of Christian Moeller
        Christian Moeller uses Amazon RedshiftAmazon Redshift

        Connected to BI (Pentaho)

        Avatar of Kovid Rathee
        Kovid Rathee uses Amazon RedshiftAmazon Redshift

        OLAP and BI

        How much does Amazon Redshift cost?
        How much does Amazon Redshift Spectrum cost?
        Pricing unavailable
        News about Amazon Redshift Spectrum
        More news