Amazon Redshift vs Hibernate: What are the differences?
What is Amazon Redshift? 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.
What is Hibernate? Idiomatic persistence for Java and relational databases. Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper.
Amazon Redshift belongs to "Big Data as a Service" category of the tech stack, while Hibernate can be primarily classified under "Object Relational Mapper (ORM)".
"Data Warehousing" is the primary reason why developers consider Amazon Redshift over the competitors, whereas "Easy ORM" was stated as the key factor in picking Hibernate.
According to the StackShare community, Amazon Redshift has a broader approval, being mentioned in 269 company stacks & 67 developers stacks; compared to Hibernate, which is listed in 87 company stacks and 74 developer stacks.
What is Amazon Redshift?
What is Hibernate?
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Looker , Stitch , Amazon Redshift , dbt
We recently moved our Data Analytics and Business Intelligence tooling to Looker . It's already helping us create a solid process for reusable SQL-based data modeling, with consistent definitions across the entire organizations. Looker allows us to collaboratively build these version-controlled models and push the limits of what we've traditionally been able to accomplish with analytics with a lean team.
For Data Engineering, we're in the process of moving from maintaining our own ETL pipelines on AWS to a managed ELT system on Stitch. We're also evaluating the command line tool, dbt to manage data transformations. Our hope is that Stitch + dbt will streamline the ELT bit, allowing us to focus our energies on analyzing data, rather than managing it.
Mybatis 로 쿼리를 만들고 조건분 분기식 for 문을 쿼리에 달아 더이상 쿼리를 알아 볼 수 없게 되었을때 이게 의마가 있나 싶었다. 그 때 한번 orm 을 써보면 어떨까 싶어 최근에 배우기 시작한 orm 이다. 정말 편하게 개발을 할 수 있는데 일조하고 있다. 다만 결국에 쿼리를 날려 맵핑을 하는데, 쿼리를 잘 모르거나 그에 대한 지식 없이 쓰다가는 망하겠구나 하는 생각이 많이 들었다.
We use a Clojure-powered wrapper around Hibernate to provide an ORM access to our data store for applications, as well as offering SSO integration and HIPAA logging functionality.
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.
Can't escape from when you're on the Java stack and deal with relational db.
Strut や Spring など Java web app flame work での Object Relation Mapperとして