Using Databases

This guide provides instructions on how to use databases with CAP applications. Out of the box-support is provided for SAP HANA, SQLite, H2 (Java only), and PostgreSQL.

This guide is available for Node.js and Java.

Use the toggle in the title bar or press v to switch.

• Setup & Configuration
  • Adding Database Packages
  • Auto-Wired Configuration
  • Custom Configuration
  • Built-in Database Support
• Providing Initial Data
  • Using .csv Files
  • Use cds add data
  • Location of CSV Files
• Querying at Runtime
  • DB-Agnostic Queries
  • Standard Operators
  • Functions Mappings for Runtime Queries
  • Session Variables
  • Native DB Queries
  • Reading LargeBinary / BLOB
• Generating DDL Files
  • Using cds compile
  • Rules for Generated DDL
  • @cds.persistence.skip
  • @cds.persistence.exists
  • @cds.persistence.table
  • @sql.prepend / append
  • Reserved Words
• Database Constraints
• Using Native Features

Setup & Configuration

Adding Database Packages

Following are cds-plugin packages for CAP Node.js runtime that support respective databases:

Database	Package	Remarks
SAP HANA Cloud	@cap-js/hana	recommended for production
SQLite	@cap-js/sqlite	recommended for development
PostgreSQL	@cap-js/postgres	maintained by community + CAP team

Follow the links above to find specific information for each.

In general, all you need to do is to install one of the database packages, as follows:

Using SQLite for development:

npm add @cap-js/sqlite -D

Using SAP HANA for production:

npm add @cap-js/hana

Prefer cds add hana ...

... which also does the equivalent of npm add @cap-js/hana but in addition cares for updating mta.yaml and other deployment resources as documented in the deployment guide.

Auto-Wired Configuration

The afore-mentioned packages use cds-plugin techniques to automatically configure the primary database with cds.env. For example, if you added SQLite and SAP HANA, this effectively results in this auto-wired configuration:

{"cds":{
  "requires": {
    "db": {
      "[development]": { "kind": "sqlite", "impl": "@cap-js/sqlite", "credentials": { "url": "memory" } },
      "[production]": { "kind": "hana", "impl": "@cap-js/hana", "deploy-format": "hdbtable" }
    }
  }
}}

In contrast to pre-CDS 7 setups this means...

1. You don't need to — and should not — add direct dependencies to driver packages, like hdb or sqlite3 anymore in your package.json files.
2. You don't need to configure cds.requires.db anymore, unless you want to override defaults brought with the new packages.

Custom Configuration

The auto-wired configuration uses configuration presets, which are automatically enabled via cds-plugin techniques. You can always use the basic configuration and override individual properties to create a different setup:

1. Install a database driver package, for example:

   npm add @cap-js/sqlite

   Add option -D if you want this for development only.

2. Configure the primary database as a required service through cds.requires.db, for example:

   {"cds":{
     "requires": {
       "db": {
         "kind": "sqlite",
         "impl": "@cap-js/sqlite",
         "credentials": {
           "url": "db.sqlite"
         }
       }
     }
   }}

The config options are as follows:

• kind — a name of a preset, like sql, sqlite, postgres, or hana
• impl — the module name of a CAP database service implementation
• credentials — an object with db-specific configurations, most commonly url

Don't configure credentials

Credentials like username and password should not be added here but provided through service bindings, for example, via cds bind.

Use cds env to inspect effective configuration

For example, running this command:

cds env cds.requires.db

→ prints:

{
  kind: 'sqlite',
  impl: '@cap-js/sqlite',
  credentials: { url: 'db.sqlite' }
}

Built-in Database Support

CAP Java has built-in support for different SQL-based databases via JDBC. This section describes the different databases and any differences between them with respect to CAP features. There's out of the box support for SAP HANA with CAP currently as well as H2 and SQLite. However, it's important to note that H2 and SQLite aren't enterprise grade databases and are recommended for non-productive use like local development or CI tests only. PostgreSQL is supported in addition, but has various limitations in comparison to SAP HANA, most notably in the area of schema evolution.

Database support is enabled by adding a Maven dependency to the JDBC driver, as shown in the following table:

Database	JDBC Driver	Remarks
SAP HANA Cloud	com.sap.cloud.db.jdbc:ngdbc	Recommended for productive use
H2	com.h2database:h2	Recommended for development and CI
SQLite	org.xerial:sqlite-jdbc	Supported for development and CI Recommended for local MTX
PostgreSQL	org.postgresql:postgresql	Supported for productive use

Learn more about supported databases in CAP Java and their configuration

Providing Initial Data

You can use CSV files to fill your database with initial data - see Location of CSV Files.

For example, in our cap/samples/bookshop application, we do so for Books, Authors, and Genres as follows:

bookshop/
├─ db/
│ ├─ data/ # place your .csv files here
│ │ ├─ sap.capire.bookshop-Authors.csv
│ │ ├─ sap.capire.bookshop-Books.csv
│ │ ├─ sap.capire.bookshop-Books.texts.csv
│ │ └─ sap.capire.bookshop-Genres.csv
│ └─ schema.cds
└─ ...

For example, in our CAP Samples for Java application, we do so for some entities such as Books, Authors, and Genres as follows:

db/
├─ data/ # place your .csv files here
│ ├─ my.bookshop-Authors.csv
│ ├─ my.bookshop-Books.csv
│ ├─ my.bookshop-Books.texts.csv
│ ├─ my.bookshop-Genres.csv
│ └─ ...
└─ index.cds

The filenames are expected to match fully qualified names of respective entity definitions in your CDS models, optionally using a dash - instead of a dot . for cosmetic reasons.

Using .csv Files

The content of these files is standard CSV content with the column titles corresponding to declared element names, like for Books:

db/data/sap.capire.bookshop-Books.csv

ID,title,author_ID,stock
201,Wuthering Heights,101,12
207,Jane Eyre,107,11
251,The Raven,150,333
252,Eleonora,150,555
271,Catweazle,170,22

Note: author_ID is the generated foreign key for the managed Association author → learn more about that in the Generating SQL DDL section.

If your content contains ...

• commas or line breaks → enclose it in double quotes "..."
• double quotes → escape them with doubled double quotes: ""...""

ID,title,descr
252,Eleonora,"""Eleonora"" is a short story by Edgar Allan Poe, first published in 1842 in Philadelphia in the literary annual The Gift."

DANGER

On SAP HANA, only use CSV files for configuration data that can't be changed by application users. → See CSV data gets overridden in the SAP HANA guide for details.

Use cds add data

Run this to generate an initial set of empty .csv files with header lines based on your CDS model:

cds add data

Location of CSV Files

CSV files can be found in the folders db/data and test/data, as well as in any data folder next to your CDS model files. When you use cds watch or cds deploy, CSV files are loaded by default from test/data. However, when preparing for production deployments using cds build, CSV files from test/data are not loaded.

Adding initial data next to your data model

The content of these 'co-located' .cds files actually doesn't matter, but they need to be included in your data model, through a using clause in another file for example.

If you need to use certain CSV files exclusively for your production deployments, but not for tests, you can achieve this by including them in a separate data folder, for example, db/hana/data. Create an index.cds file in the hana folder as outlined earlier. Then, set up this model location in a dummy cds service, for example hanaDataSrv, using the [production] profile.

"cds": {
  "requires": {
    "[production]": {
      "hanaDataSrv ": { "model": "hana" }
     }
  }
}

As a consequence, when you run cds build -–production the model folder hana is added, but it's not added when you run cds deploy or cds watch because the development profile is used by default. You can verify this by checking the cds build logs for the hana build task. Of course, this mechanism can also be used for PostgreSQL database deployments.

On SAP HANA ...

CSV and hdbtabledata files found in the src folder of your database module are treated as native SAP HANA artifacts and deployed as they are. This approach offers the advantage of customizing the hdbtabledata files if needed, such as adding a custom include_filter setting to mix initial and customer data in one table. However, the downside is that you must redundantly maintain them to keep them in sync with your CSV files.

Quite frequently you need to distinguish between sample data and real initial data. CAP supports this by allowing you to provide initial data in two places:

Location	Deployed...	Purpose
db/data	always	initial data for configurations, code lists, and similar
test/data	if not in production	sample data for tests and demos

Use the properties cds.dataSource.csv.* to configure the location of the CSV files. You can configure different sets of CSV files in different Spring profiles. This configuration reads CSV data from test/data if the profile test is active:

srv/src/main/resources/application.yaml

---
spring:
  config.activate.on-profile: test
cds:
  dataSource.csv.paths:
  - test/data/**

Querying at Runtime

Most queries to databases are constructed and executed from generic event handlers of CRUD requests, so quite frequently there's nothing to do. The following is for the remaining cases where you have to provide custom logic, and as part of it execute database queries.

DB-Agnostic Queries

At runtime, we usually construct and execute queries using cds.ql APIs in a database-agnostic way. For example, queries like this are supported for all databases:

SELECT.from (Authors, a => {
  a.ID, a.name, a.books (b => {
    b.ID, b.title
  })
})
.where ({name:{like:'A%'}})
.orderBy ('name')

At runtime, we usually construct queries using the CQL Query Builder API in a database-agnostic way. For example, queries like this are supported for all databases:

Select.from(AUTHOR)
      .columns(a -> a.id(), a -> a.name(),
               a -> a.books().expand(b -> b.id(), b.title()))
      .where(a -> a.name().startWith("A"))
      .orderBy(a -> a.name());

Standard Operators

The database services guarantee identical behavior of these operators:

• ==, = — with = null being translated to is null
• !=, <> — with != translated to IS NOT in SQLite, or to IS DISTINCT FROM in standard SQL, or to an equivalent polyfill in SAP HANA
• <, >, <=, >=, IN, LIKE — are supported as is in standard SQL

In particular, the translation of != to IS NOT in SQLite — or to IS DISTINCT FROM in standard SQL, or to an equivalent polyfill in SAP HANA — greatly improves the portability of your code.

Runtime Only

The operator mappings are available for runtime queries only, but not in CDS files.

Functions Mappings for Runtime Queries

A specified set of standard functions is supported in a database-agnostic, hence portable way, and translated to database-specific variants or polyfills. Note that these functions are only supported within runtime queries, but not in CDS files. This set of functions are by large the same as specified in OData:

• concat(x,y,...) — concatenates the given strings or numbers
• trim(x) — removes leading and trailing whitespaces
• contains(x,y) — checks whether y is contained in x, may be fuzzy
• startswith(x,y) — checks whether y starts with x
• endswith(x,y) — checks whether y ends with x
• matchespattern(x,y) — checks whether x matches regex y
• substring(x,i,n?) ¹ — extracts a substring from x starting at i (may be negative) with length n (optional; may be negative)
• indexof(x,y) ¹ — returns the index of the first occurrence of y in x
• length(x) — returns the length of string x
• tolower(x) — returns all-lowercased x
• toupper(x) — returns all-uppercased x
• ceiling(x) — rounds the input numeric parameter up to the nearest numeric value
• floor(x) — rounds the input numeric parameter down to the nearest numeric value
• round(x) — rounds the input numeric parameter to the nearest numeric value. The mid-point between two integers is rounded away from zero, i.e. 0.5 is rounded to 1 and ‑0.5 is rounded to -1.
• year(x) month(x), day(x), hour(x), minute(x), second(x), fractionalseconds(x), time(x), date(x) — returns parts of a datetime for a given cds.DateTime / cds.Date / cds.Time
• maxdatetime(x), mindatetime(x) — return the maximum or minimum datetime for a given cds.DateTime / cds.Date / cds.Time
• totalseconds(x) — returns the total seconds of a datetime for a given cds.DateTime / cds.Time
• now() — returns the current datetime
• min(x) max(x) sum(x) avg(x) count(x), countdistinct(x) — aggregate functions
• search(xs,y) — checks whether y is contained in any of xs, may be fuzzy → see Searching Data
• session_context(v) — with standard variable names → see Session Variables

¹ These functions work zero-based. E.g., substring('abcdef', 1, 3) returns 'bcd'

You have to write these functions exactly as given; all-uppercase usages aren't supported.

In addition to the standard functions, which all @cap-js database services support, @cap-js/sqlite and @cap-js/postgres also support these common SAP HANA functions, to further increase the scope for portable testing:

• years_between — Computes the number of years between two specified dates.
• months_between — Computes the number of months between two specified dates.
• days_between — Computes the number of days between two specified dates.
• seconds_between — Computes the number of seconds between two specified dates.
• nano100_between — Computes the time difference between two dates to the precision of 0.1 microseconds.

The database service implementation translates these to the best-possible native SQL functions, thus enhancing the extent of portable queries. With open source and the new database service architecture, we also have methods in place to enhance this list by custom implementation.

For the SAP HANA functions, both usages are allowed: all-lowercase as given above, as well as all-uppercase.

Runtime Only

The function mappings are available for runtime queries only, but not in CDS files.

Session Variables

The API shown below, which includes the function session_context() and specific pseudo variable names, is supported by all new database services, that is, SQLite, PostgreSQL and SAP HANA. This allows you to write respective code once and run it on all these databases:

SELECT session_context('$user.id')
SELECT session_context('$user.locale')
SELECT session_context('$valid.from')
SELECT session_context('$valid.to')

Among other things, this allows us to get rid of static helper views for localized data like localized_de_sap_capire_Books.

Native DB Queries

If required you can also use native database features by executing native SQL queries:

cds.db.run (`SELECT from sqlite_schema where name like ?`, name)

Use Spring's JDBC Template to leverage native database features as follows:

@Autowired
JdbcTemplate db;
...
db.queryForList("SELECT from sqlite_schema where name like ?", name);

Reading LargeBinary / BLOB

Formerly, LargeBinary elements (or BLOBs) were always returned as any other data type. Now, they are skipped from SELECT * queries. Yet, you can still enforce reading BLOBs by explicitly selecting them. Then the BLOB properties are returned as readable streams.

SELECT.from(Books)          //> [{ ID, title, ..., image1, image2 }]
SELECT.from(Books)          //> [{ ID, title, ... }]
SELECT(['image1', 'image2']).from(Books) //> [{ image1, image2 }]
SELECT(['image1', 'image2']).from(Books) //> [{ image1: Readable, image2: Readable }]

Read more about custom streaming in Node.js.

Generating DDL Files

When you run your server with cds watch during development, an in-memory database is bootstrapped automatically, with SQL DDL statements generated based on your CDS models.

You can also do this manually with the CLI command cds compile --to <dialect>.

When you've created a CAP Java application with cds init --java or with CAP Java's Maven archetype, the Maven build invokes the CDS compiler to generate a schema.sql file for your target database. In the default profile (development mode), an in-memory database is initialized by Spring and the schema is bootstrapped from the schema.sql file.

Learn more about adding an inital database schema.

Using cds compile

For example, given these CDS models (derived from cap/samples/bookshop):

db/schema.cds

using { Currency } from '@sap/cds/common';
namespace sap.capire.bookshop;

entity Books {
  key ID : UUID;
  title  : localized String;
  descr  : localized String;
  author : Association to Authors;
  price  : {
    amount   : Decimal;
    currency : Currency;
  }
}

entity Authors {
  key ID : UUID;
  name  : String;
  books : Association to many Books on books.author = $self;
}

srv/cat-service.cds

using { sap.capire.bookshop as my } from '../db/schema';
service CatalogService {
  entity ListOfBooks as projection on Books {
    *, author.name as author
  }
}

Generate an SQL DDL script by running this in the root directory containing both .cds files:

cds compile srv/cat-service --to sql --dialect sqlite > schema.sql

Output:

schema.sql

CREATE TABLE sap_capire_bookshop_Books (
  ID NVARCHAR(36) NOT NULL,
  title NVARCHAR(5000),
  descr NVARCHAR(5000),
  author_ID NVARCHAR(36),
  price_amount DECIMAL,
  price_currency_code NVARCHAR(3),
  PRIMARY KEY(ID)
);

CREATE TABLE sap_capire_bookshop_Authors (
  ID NVARCHAR(36) NOT NULL,
  name NVARCHAR(5000),
  PRIMARY KEY(ID)
);

CREATE TABLE sap_common_Currencies (
  name NVARCHAR(255),
  descr NVARCHAR(1000),
  code NVARCHAR(3) NOT NULL,
  symbol NVARCHAR(5),
  minorUnit SMALLINT,
  PRIMARY KEY(code)
);

CREATE TABLE sap_capire_bookshop_Books_texts (
  locale NVARCHAR(14) NOT NULL,
  ID NVARCHAR(36) NOT NULL,
  title NVARCHAR(5000),
  descr NVARCHAR(5000),
  PRIMARY KEY(locale, ID)
);

CREATE VIEW CatalogService_ListOfBooks AS SELECT
  Books.ID,
  Books.title,
  Books.descr,
  author.name AS author,
  Books.price_amount,
  Books.price_currency_code
FROM sap_capire_bookshop_Books AS Books
LEFT JOIN sap_capire_bookshop_Authors AS author
ON Books.author_ID = author.ID;

--- some more technical views skipped ...

cds compile srv/cat-service --to sql > schema.sql

Output:

schema.sql

CREATE TABLE sap_capire_bookshop_Books (
  createdAt TIMESTAMP(7),
  createdBy NVARCHAR(255),
  modifiedAt TIMESTAMP(7),
  modifiedBy NVARCHAR(255),
  ID INTEGER NOT NULL,
  title NVARCHAR(111),
  descr NVARCHAR(1111),
  author_ID INTEGER,
  genre_ID INTEGER,
  stock INTEGER,
  price DECFLOAT,
  currency_code NVARCHAR(3),
  image BINARY LARGE OBJECT,
  PRIMARY KEY(ID)
);
CREATE TABLE sap_capire_bookshop_Books (
  ID NVARCHAR(36) NOT NULL,
  title NVARCHAR(5000),
  descr NVARCHAR(5000),
  author_ID NVARCHAR(36),
  price_amount DECIMAL,
  price_currency_code NVARCHAR(3),
  PRIMARY KEY(ID)
);

CREATE TABLE sap_capire_bookshop_Authors (
  ID NVARCHAR(36) NOT NULL,
  name NVARCHAR(5000),
  PRIMARY KEY(ID)
);

CREATE TABLE sap_common_Currencies (
  name NVARCHAR(255),
  descr NVARCHAR(1000),
  code NVARCHAR(3) NOT NULL,
  symbol NVARCHAR(5),
  minorUnit SMALLINT,
  PRIMARY KEY(code)
);

CREATE TABLE sap_capire_bookshop_Books_texts (
  locale NVARCHAR(14) NOT NULL,
  ID NVARCHAR(36) NOT NULL,
  title NVARCHAR(5000),
  descr NVARCHAR(5000),
  PRIMARY KEY(locale, ID)
);

CREATE VIEW CatalogService_ListOfBooks AS SELECT
  Books_0.createdAt,
  Books_0.modifiedAt,
  Books_0.ID,
  Books_0.title,
  Books_0.author,
  Books_0.genre_ID,
  Books_0.stock,
  Books_0.price,
  Books_0.currency_code,
  Books_0.image
FROM CatalogService_Books AS Books_0;
CREATE VIEW CatalogService_ListOfBooks AS SELECT
  Books.ID,
  Books.title,
  Books.descr,
  author.name AS author,
  Books.price_amount,
  Books.price_currency_code
FROM sap_capire_bookshop_Books AS Books
LEFT JOIN sap_capire_bookshop_Authors AS author
ON Books.author_ID = author.ID;

--- some more technical views skipped ...

TIP

Use the specific SQL dialect (hana, sqlite, h2, postgres) with cds compile --to sql --dialect <dialect> to get DDL that matches the target database.

Rules for Generated DDL

A few observations on the generated SQL DDL output:

1. Tables / Views — Declared entities become tables, projected entities become views.
2. Type Mapping — CDS types are mapped to database-specific SQL types.
3. Slugified FQNs — Dots in fully qualified CDS names become underscores in SQL names.
4. Flattened Structs — Structured elements like Books:price are flattened with underscores.
5. Generated Foreign Keys — For managed to-one Associations, foreign key columns are created. For example, this applies to Books:author.

In addition, you can use the following annotations to fine-tune generated SQL.

@cds.persistence.skip

Add @cds.persistence.skip to an entity to indicate that this entity should be skipped from generated DDL scripts, and also no SQL views to be generated on top of it:

@cds.persistence.skip
entity Foo {...}                 //> No SQL table will be generated
entity Bar as select from Foo;   //> No SQL view will be generated

@cds.persistence.exists

Add @cds.persistence.exists to an entity to indicate that this entity should be skipped from generated DDL scripts. In contrast to @cds.persistence.skip a database relation is expected to exist, so we can generate SQL views on top.

@cds.persistence.exists
entity Foo {...}                 //> No SQL table will be generated
entity Bar as select from Foo;   //> The SQL view will be generated

On SAP HANA ...

If the respective entity is a user-defined function or a calculation view, one of the annotations @cds.persistence.udf or @cds.persistence.calcview also needs to be assigned. See Calculated Views and User-Defined Functions for more details.

@cds.persistence.table

Annotate an entity with @cds.persistence.table to create a table with the effective signature of the view definition instead of an SQL view.

@cds.persistence.table
entity Foo as projection on Bar {...}

All parts of the view definition not relevant for the signature (like where, group by, ...) are ignored.

Use case for this annotation: Use projections on imported APIs as replica cache tables.

@sql.prepend / append

Use @sql.prepend and @sql.append to add native SQL clauses to before or after generated SQL output of CDS entities or elements.

Example:

@sql.append: ```sql
  GROUP TYPE foo
  GROUP SUBTYPE bar
```
entity E { ...,
  @sql.append: 'FUZZY SEARCH INDEX ON'
  text: String(100);
}

@sql.append: 'WITH DDL ONLY'
entity V as select from E { ... };

Output:

CREATE TABLE E ( ...,
  text NVARCHAR(100) FUZZY SEARCH INDEX ON
) GROUP TYPE foo
GROUP SUBTYPE bar;

CREATE VIEW V AS SELECT ... FROM E WITH DDL ONLY;

The following rules apply:

• The value of the annotation must be a string literal.

• The compiler doesn't check or process the provided SQL snippets in any way. You're responsible to ensure that the resulting statement is valid and doesn't negatively impact your database or your application. We don't provide support for problems caused by using this feature.

• If you refer to a column name in the annotation, you need to take care of a potential name mapping yourself, for example, for structured elements.

• Annotation @sql.prepend is only supported for entities translating to tables. It can't be used with views nor with elements.

• For SAP HANA tables, there's an implicit @sql.prepend: 'COLUMN' that is overwritten by an explicitly provided @sql.prepend.

• Both @sql.prepend and @sql.append are disallowed in SaaS extension projects.

If you use native database clauses in combination with @cds.persistence.journal, see Schema Evolution Support of Native Database Clauses.

Creating a Row Table on SAP HANA

By using @sql.prepend: 'ROW', you can create a row table:

@sql.prepend: 'ROW'
entity E {
  key id: Integer;
}

Run cds compile - 2 hdbtable on the previous sample and this is the result:

ROW TABLE E (
  id INTEGER NOT NULL,
  PRIMARY KEY(id)
)

Learn more about Columnar and Row-Based Data Storage

Reserved Words

The CDS compiler and CAP runtimes provide smart quoting for reserved words in SQLite and in SAP HANA so that they can still be used in most situations. But in general reserved words cannot be used as identifiers. The list of reserved words varies per database.

Find here a collection of resources on selected databases and their reference documentation:

• SAP HANA SQL Reference Guide for SAP HANA Platform (Cloud Version)
• SAP HANA SQL Reference Guide for SAP HANA Cloud
• SQLite Keywords
• H2 Keywords/Reserved Words
• PostgreSQL SQL Key Words

There are also reserved words related to SAP Fiori.

Database Constraints

The information about foreign key relations contained in the associations of CDS models can be used to generate foreign key constraints on the database tables. Within CAP, referential consistency is established only at commit. The "deferred" concept for foreign key constraints in SQL databases allows the constraints to be checked and enforced at the time of the COMMIT statement within a transaction rather than immediately when the data is modified, providing more flexibility in maintaining data integrity.

Enable generation of foreign key constraints on the database with:

cds.features.assert_integrity = db

Database constraints are not supported for H2

Referential constraints on H2 cannot be defined as "deferred", which is needed for database constraints within CAP.

With that switched on, foreign key constraints are generated for managed to-one associations. For example, given this model:

entity Books {
  key ID : Integer; ...
  author : Association to Authors;
}
entity Authors {
  key ID : Integer; ...
}

The following Books_author constraint would be added to table Books:

CREATE TABLE Authors (
  ID INTEGER NOT NULL,  -- primary key referenced by the constraint
  ...,
  PRIMARY KEY(ID)
);
CREATE TABLE Books (
  ID INTEGER NOT NULL,
  author_ID INTEGER,    -- generated foreign key field
  ...,
  PRIMARY KEY(ID),
  CONSTRAINT Books_author   -- constraint is explicitly named
    FOREIGN KEY(author_ID)  -- link generated foreign key field author_ID ...
    REFERENCES Authors(ID)  -- ... with primary key field ID of table Authors
    ON UPDATE RESTRICT
    ON DELETE RESTRICT
    VALIDATED           -- validate existing entries when constraint is created
    ENFORCED            -- validate changes by insert/update/delete
    INITIALLY DEFERRED  -- validate only at commit
)

No constraints are generated for...

• Unmanaged associations or compositions
• To-many associations or compositions
• Associations annotated with @assert.integrity: false
• Associations where the source or target entity is annotated with @cds.persistence.exists or @cds.persistence.skip

If the association is the backlink of a composition, the constraint's delete rule changes to CASCADE. That applies, for example, to the parent association in here:

entity Genres {
  key ID   : Integer;
  parent   : Association to Genres;
  children : Composition of many Genres on children.parent = $self;
}

As a special case, a referential constraint with delete cascade is also generated for the text table of a localized entity, although no managed association is present in the texts entity.

Add a localized element to entity Books from the previous example:

entity Books {
  key ID : Integer; ...
  title : localized String;
}

The generated text table then is:

CREATE TABLE Books_texts (
  locale NVARCHAR(14) NOT NULL,
  ID INTEGER NOT NULL,
  title NVARCHAR(5000),
  PRIMARY KEY(locale, ID),
  CONSTRAINT Books_texts_texts // [!code focus]
    FOREIGN KEY(ID)
    REFERENCES Books(ID)
    ON UPDATE RESTRICT
    ON DELETE CASCADE
    VALIDATED
    ENFORCED
    INITIALLY DEFERRED
)

Database constraints aren't intended for checking user input

Instead, they protect the integrity of your data in the database layer against programming errors. If a constraint violation occurs, the error messages coming from the database aren't standardized by the runtimes but presented as-is.

→ Use @assert.target for corresponding input validations.

Using Native Features

In general, the CDS 2 SQL compiler doesn't 'understand' SQL functions but translates them to SQL generically as long as they follow the standard call syntax of function(param1, param2). This allows you to use native database functions inside your CDS models.

Example:

entity BookPreview as select from Books {
  IFNULL (descr, title) as shorttext   //> using HANA function IFNULL
};

The OVER clause for SQL Window Functions is supported, too:

entity RankedBooks as select from Books {
  name, author,
  rank() over (partition by author order by price) as rank
};

Using Native Functions with Different DBs

In case of conflicts, follow these steps to provide different models for different databases:

1. Add database-specific schema extensions in specific subfolders of ./db:

   db/sqlite/index.cds

   using { AdminService } from '..';
   extend projection AdminService.Authors with {
      strftime('%Y',dateOfDeath)-strftime('%Y',dateOfBirth) as age : Integer
   }

   db/hana/index.cds

   using { AdminService } from '..';
   extend projection AdminService.Authors with {
      YEARS_BETWEEN(dateOfBirth, dateOfDeath) as age : Integer
   }

2. Add configuration in specific profiles to your package.json, to use these database-specific extensions:

   { "cds": { "requires": {
     "db": {
      "kind": "sql",
      "[development]": { "model": "db/sqlite" },
      "[production]": { "model": "db/hana" }
    }
   }}}

CAP samples demonstrate this in cap/samples/fiori.
There's also a code tour available for that.