Amazon Redshift vs Snowflake vs Treasure Data

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Amazon Redshift

1.3K
1.1K
+ 1
103
Snowflake

652
774
+ 1
16
Treasure Data

24
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+ 1
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Pros of Amazon Redshift
Pros of Snowflake
Pros of Treasure Data
  • 37
    Data Warehousing
  • 27
    Scalable
  • 16
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
  • 1
    Cheap and reliable
  • 1
    Isolation
  • 1
    Best Cloud DW Performance
  • 1
    Fast columnar storage
  • 3
    Good Performance
  • 2
    User Friendly
  • 2
    Serverless
  • 2
    Great Documentation
  • 2
    Multicloud
  • 2
    Public and Private Data Sharing
  • 1
    Usage based billing
  • 1
    Innovative
  • 1
    Economical
  • 2
    Scaleability, less overhead
  • 2
    Makes it easy to ingest all data from different inputs
  • 1
    Responsive to our business requirements, great support

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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.

What is Snowflake?

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

What is Treasure Data?

Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.

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What companies use Amazon Redshift?
What companies use Snowflake?
What companies use Treasure Data?

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What tools integrate with Amazon Redshift?
What tools integrate with Snowflake?
What tools integrate with Treasure Data?

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What are some alternatives to Amazon Redshift, Snowflake, and Treasure Data?
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.
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.
See all alternatives