The world of SQL query builders is evolving rapidly, and one of the most promising tools in modern TypeScript and JavaScript development is Kysely — a type-safe SQL query builder that provides a clean, expressive, and strongly typed interface for database interaction. However, as developers transition from traditional SQL statements or other libraries like Knex or Prisma, they often encounter subtle pitfalls when handling complex SQL functions within Kysely. One such challenge that has confused many is the “Kysely date_trunc is not unique” issue.
This issue arises primarily when developers attempt to truncate date or timestamp values using PostgreSQL’s date_trunc function (or equivalent in other SQL dialects) within Kysely’s query structure, only to find unexpected errors or duplicate handling problems. The root cause often ties to how Kysely represents, aliases, and groups by these computed date expressions — especially when used within aggregation queries or joins.
In this article, we will explore what this error really means, why it happens, and how to fix or work around it efficiently. We will break down the date_trunc function in SQL, examine how Kysely compiles SQL under the hood, discuss grouping and aliasing rules, and provide step-by-step examples to help you master this concept. Finally, we’ll answer some frequently asked questions and close with a practical summary to help you write safer, cleaner, and more maintainable queries.
1. Understanding Kysely – A Brief Overview
Kysely is a type-safe and expressive SQL query builder designed for TypeScript and JavaScript developers who want the power of SQL with the safety of static typing. Unlike traditional query builders that focus solely on string-based SQL generation, Kysely provides a declarative, composable, and fully typed API that allows you to write SQL queries as fluent TypeScript objects and functions.
At its core, Kysely eliminates a common pain point — runtime SQL errors due to incorrect column names, mismatched data types, or syntax mistakes. The type system of Kysely infers your schema from the defined database interface, so invalid references are caught at compile time rather than runtime. This helps developers maintain large codebases with confidence, especially in backend systems where query correctness and performance are critical.
However, because Kysely is still relatively new and offers flexibility across multiple SQL dialects (like PostgreSQL, MySQL, and SQLite), not all SQL functions behave identically when expressed through its builder syntax. Some PostgreSQL-specific functions like date_trunc, to_char, or interval operations require careful handling to ensure proper SQL generation. This is where problems such as “date_trunc is not unique” may arise if not properly aliased or grouped.
2. The Role of date_trunc in SQL
Before diving into Kysely-specific issues, it’s important to understand what the SQL function date_trunc does. In PostgreSQL and other relational databases, date_trunc is used to truncate a timestamp or date to a specific level of precision, such as hour, day, week, or month.
For example:
This query groups user creation events by day, producing counts of users per calendar day. The function date_trunc('day', created_at) cuts off the time component, giving a clean boundary for aggregation.
The challenge arises when this function is used in query builders or ORMs that require explicit aliasing or type inference. In pure SQL, you can easily use aliases like AS day, but in a type-safe builder, you need to ensure that the resulting computed column is named, typed, and grouped consistently.
If this is not done correctly in Kysely, it can lead to duplicate entries, conflicting column identifiers, or ambiguous groupings — manifesting in errors such as “date_trunc is not unique.”
3. Why “Kysely date_trunc Is Not Unique” Occurs
The error message “date_trunc is not unique” typically arises when Kysely generates SQL with non-unique expressions in the SELECT or GROUP BY clause. This often happens when a developer uses the same date_trunc function multiple times without aliasing or when the resulting column name conflicts with another field in the query.
Consider this simplified Kysely example:
This looks correct at first glance — but if another field or nested join introduces the same date_trunc expression, Kysely’s internal builder may not differentiate between them. Since each `sql“ fragment is treated as a separate SQL expression node, the compiler may generate a duplicate alias or fail to enforce uniqueness in grouping.
Moreover, PostgreSQL requires that every non-aggregated field in the SELECT clause appear in the GROUP BY clause exactly once. If date_trunc is repeated or not correctly aliased, the database engine can reject the query or produce unexpected duplicate records
4. Aliasing: The Key to Fixing the Issue
The simplest and most reliable way to prevent “Kysely date_trunc is not unique” is through explicit aliasing. Aliasing ensures that every computed column or expression has a unique identifier in both the SELECT and GROUP BY clauses.
Here’s a corrected example:
By aliasing the date_trunc result as 'order_day', Kysely can safely refer to it in the groupBy() clause without re-evaluating the function or confusing multiple expressions. This approach is both safer and cleaner, and it aligns with how PostgreSQL handles derived columns in aggregation queries.
In larger projects, consistent naming conventions for time-based aggregations (like created_day, created_week, created_month) help maintain clarity and prevent duplicate alias issues across queries.
5. Using Helper Functions to Simplify date_trunc
When developers need to repeatedly truncate dates across multiple queries, manually writing the same sql\date_trunc(…)“ expression can be error-prone. Instead, you can abstract this logic into a small helper function that generates properly aliased and typed SQL fragments.
For example:
Then you can use it consistently across your Kysely queries:
This approach improves maintainability and ensures that alias naming remains consistent. If the date_trunc logic ever needs to change (for example, from ‘day’ to ‘week’), you only need to update the helper once.
Helper functions are especially beneficial in analytics-heavy applications where multiple datasets require similar temporal groupings. They also make your code more readable and self-documenting.
6. Advanced Grouping and Joins with Truncated Dates
In more complex queries involving joins or multiple time-based groupings, date_trunc can appear in several parts of the query. For example, when comparing daily order counts to daily customer signups, developers might need to truncate both orders.created_at and users.created_at to the same precision.
Here’s an example:
Without consistent aliasing (order_day in this case), PostgreSQL might complain about ambiguous or non-unique group expressions, and Kysely could duplicate expressions in the generated SQL.
Always alias computed columns that you plan to group by, and never rely on raw SQL fragments appearing multiple times without names. This ensures clarity and avoids subtle logic errors.
7. Best Practices for Handling SQL Functions in Kysely
To prevent issues like “date_trunc is not unique,” adopt a few best practices when writing Kysely queries:
-
Always Alias Computed Columns: Give every
sqlfragment a clear, unique alias when it appears inSELECT. -
Use Aliases in Grouping: Always refer to grouped columns by their alias instead of repeating the expression.
-
Encapsulate Common SQL Functions: Use helper functions for recurring patterns like
date_trunc. -
Avoid Repeating SQL Fragments: Never duplicate an identical computed field in the same query without aliasing.
-
Test the Generated SQL: Use Kysely’s
.compile()or.toSql()methods to inspect the final SQL output before running it. -
Keep Schema Types Accurate: Make sure your database interface reflects timestamp and date fields correctly so TypeScript can infer types.
Following these conventions will drastically reduce errors and make your Kysely codebase cleaner and easier to maintain.
8. Debugging “Not Unique” Errors in Kysely
When you encounter the “not unique” error, the best debugging approach is to inspect the generated SQL query that Kysely produces. You can do this by using the .compile() method:
Reviewing the actual SQL string will often reveal duplicated or ambiguous expressions. Look for repeated date_trunc calls or missing aliases. Once identified, refactor the query to give every expression a distinct alias or adjust your group-by logic.
Additionally, using PostgreSQL’s error messages as guidance can help pinpoint which field or alias is causing duplication. Logging the query in development mode (without executing it) is a safe way to troubleshoot without affecting your production database.
9. Common Misconceptions About date_trunc in Kysely
A frequent misunderstanding is that date_trunc itself causes the problem, when in fact it’s how it’s used within Kysely’s builder. The function itself works flawlessly in raw SQL — the issue stems from aliasing, grouping, and how Kysely interprets SQL fragments as unique nodes in its internal tree.
Another misconception is that you can reuse the same raw SQL expression multiple times without conflict. In Kysely, each invocation of sql\`creates a new object, even if the text is identical. That means two identicaldate_trunc(‘day’, created_at)fragments are treated as distinct expressions. This is why aliasing or reusing the samesql.ref` variable is critical.
Finally, some assume Kysely automatically handles all SQL function uniqueness — but because SQL allows flexible syntax and Kysely is type-safe, developers are expected to explicitly define identifiers and structure for complex functions.
10. Real-World Example: Time-Based Reporting
In real-world analytics dashboards, you might aggregate data by time intervals for reporting purposes — say, daily active users, weekly sales, or monthly retention.
For example:
This query will run safely as long as you use a unique alias (week_start). If you later add another computed field using the same date_trunc without aliasing, you risk hitting the “not unique” issue again.
By standardizing how date truncation is handled (via helper utilities, aliases, or even database views), you ensure that all analytics queries remain consistent and error-free.
Frequently Asked Questions (FAQ)
Q1: What does “Kysely date_trunc is not unique” mean?
It means that your query contains repeated or conflicting SQL expressions — often the same date_trunc call — without a unique alias or grouping, causing ambiguity in SQL generation.
Q2: Is this a bug in Kysely?
No, it’s not a bug. It’s a result of how SQL expressions are represented internally in Kysely. The developer needs to provide explicit aliases or reuse consistent references to avoid duplicates.
Q3: Can I fix it by using raw SQL strings?
Yes, but it’s not recommended. Instead, use `sql“ fragments with proper aliasing to maintain type safety. Falling back to raw SQL removes Kysely’s main benefits.
Q4: Does this issue occur only in PostgreSQL?
Mostly yes, since date_trunc is PostgreSQL-specific. However, similar issues can appear in other dialects if equivalent date functions are used without aliasing.
Q5: What is the best way to prevent this issue?
Always alias computed columns, use helper functions, and test generated SQL before execution. Consistent naming conventions help prevent collisions.
Conclusion
The “Kysely date_trunc is not unique” issue is a perfect example of how powerful tools require thoughtful use. Kysely gives developers the power of SQL with the safety of TypeScript, but it also demands precision in how expressions and aliases are defined. The underlying cause is not a flaw in Kysely itself, but a misunderstanding of how SQL grouping and aliasing operate within its type-safe context.
By learning to properly alias computed columns, reuse helper functions, and inspect compiled SQL, developers can write elegant, maintainable, and performant queries without running into confusing errors. More importantly, mastering this pattern improves your overall SQL literacy — a valuable skill that extends beyond any specific library or framework.
In short: Kysely + proper aliasing = clean, unique, and predictable queries. Handle your date_trunc logic carefully, and you’ll enjoy all the benefits of type-safe, efficient SQL generation without the headaches of ambiguous expressions or runtime errors.
