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Amazon Redshift

Fast, fully managed, petabyte-scale data warehouse service
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What is 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.
Amazon Redshift is a tool in the Big Data as a Service category of a tech stack.

Who uses Amazon Redshift?

474 companies reportedly use Amazon Redshift in their tech stacks, including Amazon, CRED, and Nubank.

999 developers on StackShare have stated that they use Amazon Redshift.

Amazon Redshift Integrations

MySQL, SQLite, Metabase, Amplitude, and Oracle PL/SQL are some of the popular tools that integrate with Amazon Redshift. Here's a list of all 131 tools that integrate with Amazon Redshift.
Pros of Amazon Redshift
Data Warehousing
Backed by Amazon
Cheap and reliable
Best Cloud DW Performance
Fast columnar storage
Decisions about Amazon Redshift

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon Redshift in their tech stack.

Needs advice
Amazon RedshiftAmazon Redshift

please help me understand the difference in syntax between MySQL and Amazon Redshift . They have the difference or they are completely the same?

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Needs advice
AWS LambdaAWS Lambda

I have data stored in Amazon S3 bucket in parquet file format.

I want this data to be copied from S3 to Amazon Redshift, so I use copy commands to achieve this. But, I need to do this manually. I want to achieve this with some sort of automation such that if any new file comes into S3, it should be copied to the required table in redshift. Can you suggest what different approaches I can use?

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Hi all,

Currently, we need to ingest the data from Amazon S3 to DB either Amazon Athena or Amazon Redshift. But the problem with the data is, it is in .PSV (pipe separated values) format and the size is also above 200 GB. The query performance of the timeout in Athena/Redshift is not up to the mark, too slow while compared to Google BigQuery. How would I optimize the performance and query result time? Can anyone please help me out?

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Blog Posts

Jul 9 2019 at 7:22PM

Blue Medora

DockerPostgreSQLNew Relic+8

Amazon Redshift's Features

  • Optimized for Data Warehousing- It uses columnar storage, data compression, and zone maps to reduce the amount of IO needed to perform queries. Redshift has a massively parallel processing (MPP) architecture, parallelizing and distributing SQL operations to take advantage of all available resources.
  • Scalable- With a few clicks of the AWS Management Console or a simple API call, you can easily scale the number of nodes in your data warehouse up or down as your performance or capacity needs change.
  • No Up-Front Costs- You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing.
  • Fault Tolerant- Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3.
  • SQL - Amazon Redshift is a SQL data warehouse and uses industry standard ODBC and JDBC connections and Postgres drivers.
  • Isolation - Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster.
  • Encryption – With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware-acccelerated AES-256 encryption for data at rest.<br>

Amazon Redshift Alternatives & Comparisons

What are some alternatives to Amazon Redshift?
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
With it , 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.
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.
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.
See all alternatives

Amazon Redshift's Followers
1353 developers follow Amazon Redshift to keep up with related blogs and decisions.