JSON support in PostgreSQL was introduced in 9.2 and has steadily improved in every release going forward. Often times an external system is providing data as JSON, so it might be a temporary store before data is ingested into other parts of the system. For example, Stripe transactions. If your data set has nested objects (single or multi-level), in some cases, it is easier to handle them in JSON instead of denormalizing the data into columns or multiple tables. We discuss more about this approach in section “JSON Patterns & Antipatterns” below. Note: If a particular key is always present in your document, it might make sense to store it as a first class column. If you store each of the keys as columns, it will result in frequent DML operations – this can be difficult when your data set is large – for example, event tracking, analytics, tags, etc. Storing your data in JSON is useful when your schema is fluid and is changing frequently. One of the main reasons to store data using the JSON format is schema flexibility. Why should a relational database even care about unstructured data? It turns out that there are a few scenarios where it is useful.
MongoDB webinar in partnership with PostgresConf to learn more on the topic, and check out our SlideShare page to download the slides. You can also check out our Working with JSON Data in PostgreSQL vs.
POSTGRESQL JSON FUNCTIONS HOW TO
In this post, we are going to show you tips and techniques on how to effectively store and index JSON data in PostgreSQL. JSON is the most common format used by web services to exchange data, store documents, unstructured data, etc. It is an open standard format which organizes data into key/value pairs and arrays detailed in RFC 7159. JSON stands for JavaScript Object Notation.
0 kommentar(er)
