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InfoQ Homepage News Snowflake Announces General Availability of their Cloud Data Warehouse Offering

Snowflake Announces General Availability of their Cloud Data Warehouse Offering

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Snowflake Computing has announced the general availability of their Snowflake Elastic Data Warehouse, a software as a service offering that provides a SQL data warehouse on top of Amazon Web Services.

In a post from October 2014 Curt Monash explains that the service "is built from scratch (as opposed, to for example, being based on PostgreSQL or Hadoop)" and "is columnar and append-only, as has become common for analytic RDBMS". "Data is stored in compressed 16 megabyte files on Amazon S3, and pulled into Amazon EC2 servers for query execution on an as-needed basis". Additionally, while "Snowflake has no indexes ... it does have zone maps, aka data skipping" which allows it to skip files that are not necessary to service a query.

Snowflake's strengths stem from three core system features. First, Snowflake is a fully managed SaaS offering which reduces the operational burden to near zero. While services like Amazon's Redshift have greatly reduced the burden of creating a data warehouse there is still an operational overhead to managing and scaling Redshift on an ongoing basis.

Second Snowflake is built to support a combination of both structured and semi-structured data. For instance, it can ingest any data in JSON, XML, or Avro format, all of which support nesting and repeated data types. This allows snowflake to move beyond the typical data warehouse use cases and encroach on Hadoop and other semi-structured use cases.

Finally, the elasticity of the service brings a new and interesting pricing model to the data warehouse market. Pricing is based on data storage size and per hour compute usage. If compute is not needed (say during over night hours) you can simply scale down the compute until it is required again. Redshift provides similar functionality, using snapshot and restore, but restores can take a significant amount of time to copy the data back to the Redshift hosts. By contrast, Snowflake can spin up much more quickly since it copies data to the hosts as needed.

In a separate announcement Snowflake also disclosed $45 million in new funding from Altimeter Capital, Redpoint Ventures, Sutter Hill Ventures and Wing Ventures. This builds upon their previous funding round in October of 2014 when Snowflake raised a total of $26 million in funding from Redpoint Ventures, Sutter Hill Ventures and Wing Ventures.

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  • SQL Industry Standard is obsolete and out of business.

    by Ilya Geller,

    • SQL Industry Standard is obsolete and out of business.

      by Ilya Geller,

      Your message is awaiting moderation. Thank you for participating in the discussion.

      Snowflaces uses SQL.
      SQL, Structured Query Language Industrial Standard obtains and uses patterns from EXTERNAL queries and statistics on how often they are used; neither the queries, nor patterns, nor statistics have anything in common with data itself.
      I, however, discovered and patented how to structure any data without SQL, the queries - INTERNALLY: Language has its own INTERNAL parsing, indexing and statistics and can be structured INTERNALLY. (For more details please browse on my name ‘Ilya Geller’.)
      For instance, there are two sentences:
      a) 'Sam!’
      b) 'A loud ringing of one of the bells was followed by the appearance of a smart chambermaid in the upper sleeping gallery, who, after tapping at one of the doors, and receiving a request from within, called over the balustrades -'Sam!'.'
      Evidently, that the 'Sam' has different importance into both sentences, in regard to extra information in both. This distinction is reflected as the phrases, which contain 'Sam', weights: the first has 1, the second – 0.08; the greater weight signifies stronger emotional ‘acuteness’; where the weight refers to the frequency that a phrase occurs in relation to other phrases.
      My structuring transforms the data itself to a new format, which computer can understand.
      SQL cannot produce the above statistics and has no my other novelties – SQL depicts data from outside, and no portrait can create an ideal representation of its object - SQL Industry Standard is obsolete and out of business.

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