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| stage | group | info |
|---|---|---|
| Data Stores | Database | To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments |
Serializing Data
Summary: don't store serialized data in the database, use separate columns and/or tables instead. This includes storing of comma separated values as a string.
Rails makes it possible to store serialized data in JSON, YAML or other formats. Such a field can be defined as follows:
class Issue < ActiveRecord::Model
serialize :custom_fields
end
While it may be tempting to store serialized data in the database there are many problems with this. This document outlines these problems and provide an alternative.
Serialized Data Is Less Powerful
When using a relational database you have the ability to query individual fields, change the schema, index data, and so forth. When you use serialized data all of that becomes either very difficult or downright impossible. While PostgreSQL does offer the ability to query JSON fields it is mostly meant for very specialized use cases, and not for more general use. If you use YAML in turn there's no way to query the data at all.
Waste Of Space
Storing serialized data such as JSON or YAML ends up wasting a lot of space. This is because these formats often include additional characters (for example, double quotes or newlines) besides the data that you are storing.
Difficult To Manage
There comes a time where you must add a new field to the serialized data, or change an existing one. Using serialized data this becomes difficult and very time consuming as the only way of doing so is to re-write all the stored values. To do so you would have to:
- Retrieve the data
- Parse it into a Ruby structure
- Mutate it
- Serialize it back to a String
- Store it in the database
On the other hand, if one were to use regular columns adding a column would be:
ALTER TABLE table_name ADD COLUMN column_name type;
Such a query would take very little to no time and would immediately apply to all rows, without having to re-write large JSON or YAML structures.
Finally, there comes a time when the JSON or YAML structure is no longer sufficient and you must migrate away from it. When storing only a few rows this may not be a problem, but when storing millions of rows such a migration can take hours or even days to complete.
Relational Databases Are Not Document Stores
When storing data as JSON or YAML you're essentially using your database as if it were a document store (for example, MongoDB), except you're not using any of the powerful features provided by a typical RDBMS nor are you using any of the features provided by a typical document store (for example, the ability to index fields of documents with variable fields). In other words, it's a waste.
Consistent Fields
One argument sometimes made in favour of serialized data is having to store widely varying fields and values. Sometimes this is truly the case, and then perhaps it might make sense to use serialized data. However, in 99% of the cases the fields and types stored tend to be the same for every row. Even if there is a slight difference you can still use separate columns and just not set the ones you don't need.
The Solution
The solution is to use separate columns and/or separate tables. This allows you to use all the features provided by your database, it makes it easier to manage and migrate the data, you conserve space, you can index the data efficiently and so forth.