![]() Now, this SUPER type allows us to directly store semi-structured data into one column and one record and start data analytics immediately. Before storing data in Redshift, we had to transform semi-structured data included in each record with other services and technologies. By leveraging this platform, we find insights to assess and enhance our internet media from data. “We use Redshift as our data analytics platform. Livesense solutions include Machbaito, Tenshoku Kaigi, and IESHIL, which help users make critical decisions on finding temporary jobs, next jobs, and real estate, respectively. Livesense is one of the leading Japan-based companies dealing with internet media on human resources, real estate, and more. This allows us to immediately start exploratory analysis.” -Keiko Hara, Software Engineer at Sony. Since the SUPER type frees us from multiple data schema updates, we can reduce operational cost by 60% and improve ingestion performance for semi-structured data without schema definition. Because of the wide variety of formats used by various products and services, schema changes and additions were frequent and time-consuming. Previously, when loading data to Redshift, we had to examine the data structure and predefine the schema. “We use Redshift as our data warehouse for analysis of various products and services. Sony uses data to accelerate their creation and enhancement of products and services. From game and network services to music, pictures, electronics, image sensors, and financial services, Sony’s purpose is to fill the world with emotion through the power of creativity and technology. Sony Corporation (Sony) is a creative entertainment company with a solid foundation of technology. SUPER is a game changer for us to use a PartiQL-style SQL accessor to query semi-structured data seamlessly with a much better developer experience and sometimes even better access speed.” -Steven Moy, Software Engineer at Yelp Sony That only allows us to use json_extract to access the stored JSON document for analytics. To avoid intensive data engineering to flatten their schema, we may store the JSON document as varchar. Native JSON data often appears in our infrastructure edge environment. “We are excited to see the Amazon Redshift SUPER data type general availability. ![]() Many Yelp microservices generate JSON-based logs to power subsequent data mining usage. Yelp is a local-search service powered by a crowd-sourced review forum, with more than 148 million reviews from around the world. Here are some of the ways they are taking advantage. Customer use casesĭuring the past four months of preview availability, customers from a broad range of industries have used JSON and semi-structured data processing with Amazon Redshift. Today, we’re excited to announce the general availability of the SUPER data type and PartiQL support in Amazon Redshift. SUPER and PartiQL together enable you to achieve advanced analytics that combine classic structured SQL data (such as strings, numerics, and timestamps) and semi-structured data with superior performance, flexibility, and ease of use. This includes a new data type, SUPER, which allows you to store JSON and other semi-structured data in Amazon Redshift tables, and support for the PartiQL query language, which allows you to seamlessly query and process the semi-structured data. At AWS re:Invent 2020, we announced the preview of native support for JSON and semi-structured data in Amazon Redshift.
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