In Microsoft Dynamics 365 Finance
& Operations (F&O), tables form the backbone of the entire data
model.
They define how business information is stored, related, and secured across the
system.
A poorly designed table can cause performance
bottlenecks, data inconsistencies, and upgrade challenges.
In this article, we’ll explore the essential best practices every X++
developer should follow when creating or customizing tables.
Use
the Right Table Type
Choosing the correct table type
is critical for ensuring that your data behaves as intended.
|
Table Type |
Use When |
|
Regular |
For master or transactional data |
|
InMemory |
For temporary data that doesn’t need to be stored in the
database |
|
TempDB |
For temporary data that can be queried using SQL joins |
|
Miscellaneous |
For special use cases such as parameters or framework
tables |
Tip: Use TempDB tables when you
need to perform queries or joins on temporary data, as they are SQL-backed and
faster for large datasets.
Use Proper Table Relations
Defining relations between
tables ensures referential integrity, improves lookups, and simplifies
form and entity development.
Instead of validating relationships through code, always define proper table
relations in the AOT.
Table
Relation Types in Dynamics 365 F&O
1.
Normal Relation
A Normal Relation defines a
direct link between fields in two tables, without additional conditions.
Multiple field pairs can be included.
Condition Example:
Table1.Field
= Table2.Field
Use Case: Basic one-to-one or one-to-many relationships between
tables.
2.
Field Fixed Relation
A Field Fixed Relation
filters records in the primary table based on a fixed field value,
usually an enum.
Only records that meet the condition are included in the relationship.
Condition Example:
Table.Field
= <EnumValue>
Use Case: When you want to filter the current table by enum type —
e.g., showing footballers when PlayerType ==
Footballer.
3.
Related Field Fixed Relation
A Related Field Fixed Relation
filters records in the related (foreign) table using a fixed value or
enum.
Condition Example:
<EnumValue>
= Table.Field
Use Case: When you need to limit which records are retrieved from the
related table — for example, only showing related records with a specific enum
value.
4.
Foreign Key Relation
A Foreign Key Relation
defines a formal connection between a foreign key field in the current
table and the primary key of another (parent) table.
This enforces referential integrity and enables system features such as
lookups, IntelliSense, and cascade delete behaviors.
Optimize
Indexes
Indexes are essential for query
performance, but having too many can slow down inserts and updates.
Choose your indexes wisely based on usage patterns.
|
Index Type |
Purpose |
Unique |
|
Primary Index |
Uniquely identifies each record |
Yes |
|
Cluster Index |
Determines physical storage order in SQL |
No |
|
Replacement Key |
Displays user-friendly values in lookups |
N/A |
|
Alternate Key |
Provides an additional unique identifier |
Yes |
Apply
Field Groups for Reuse
Field Groups help organize and reuse related fields across forms, data
entities, and reports — ensuring consistency and saving development time.
Common Examples:
- AutoReport
→ fields used for reporting
- Overview
→ summary fields for list pages
- Details
→ complete record fields for detailed views
Tip: Define meaningful field groups
early. This makes form design faster and improves UI consistency across the
application.
Use Table Methods for Business Logic
Table methods allow you to
encapsulate business logic directly within the table — improving reusability
and maintainability.
Common Methods:
- initValue()
– set default field values
- validateWrite()
– validate before insert/update
- modifiedField()
– trigger logic when a field changes
- insert(),
update(),
delete()
– manage data persistence
Set
the Appropriate Caching Strategy
Caching improves performance by
reducing database hits — but only if configured properly.
Cache
Types
None
No caching is maintained.
Use when data changes frequently, or when it’s critical to always read the
latest data directly from the database.
EntireTable
When the first select runs, all records are loaded into the cache.
Subsequent queries read from memory until the cache is invalidated by an
insert, update, or delete.
Found
Only successful queries (those
returning data) are cached.
If a record exists in the cache, it’s fetched from memory; otherwise, it’s retrieved
from the database and added to the cache.
Best suited for static or master data tables that rarely change.
FoundAndEmpty
Both successful and unsuccessful
queries are cached — even if they return no data.
Prevents repeated database lookups for the same non-existing records.
forUpdate operations
update both the database and the cache.
NotInTTS
Caching is maintained within a
transaction scope (TTS).
During an active transaction (ttsBegin / ttsCommit), external caches are ignored.
Records are select-locked, ensuring consistency throughout the transaction.
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