Google BigQuery vs Hibernate: What are the differences?
Developers describe Google BigQuery as "Analyze terabytes of data in seconds". 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.. On the other hand, Hibernate is detailed as "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.
Google BigQuery can be classified as a tool in the "Big Data as a Service" category, while Hibernate is grouped under "Object Relational Mapper (ORM)".
"High Performance" is the top reason why over 17 developers like Google BigQuery, while over 9 developers mention "Easy ORM" as the leading cause for choosing Hibernate.
According to the StackShare community, Google BigQuery has a broader approval, being mentioned in 156 company stacks & 39 developers stacks; compared to Hibernate, which is listed in 85 company stacks and 72 developer stacks.
What is Google BigQuery?
What is Hibernate?
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I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.
What's nice too is that it has SQL-based ML tools, and it has great GIS support!
BigQuery allows our team to pull reports quickly using a SQL-like queries against our large store of data about social sharing. We use the information throughout the company, to do everything from making internal product decisions based on usage patterns to sharing certain kinds of custom reports with our publishers.
Aggregation of user events and traits across a marketing website, SaaS web application, user account provisioning backend and Salesforce CRM. Enables full-funnel analysis of campaign ROI, customer acquisition, engagement and retention at both the user and target account level.
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.
Google's insanely fast, feature-rich, zero-maintenance column store. Used for real-time customer data queries.
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