DB Conditions

Conditions decide which records a database block reads, updates or deletes. The same editor is used by DB Get All, DB Get Single, DB Row Exists, DB Count, DB Update and DB Delete.

Operators

Operator	Value	Matches records where the column…
= != > >= < <=	one value	compares to the value
in / not in	a list	is / is not one of the values
contains / starts with / ends with	text	contains / starts with / ends with the text, ignoring upper and lower case
between	two values: min, max	is between the two, including both ends
is null / is not null	none	has no value / has a value
exists / not exists	none	has the field at all (MongoDB only)

Lists (for in, not in and between) can be typed as comma-separated text — active, pending — or come from an expression that returns an array, such as js:getRequestBody().ids. Use an expression when a value itself contains a comma.

• An empty list with in matches nothing, and with not in matches everything.
• A list may not contain null, and between needs exactly two values; either mistake stops the block with an error instead of quietly matching the wrong records. To match empty values, use is null.
• not in never matches a record whose value is empty (null) — the same on every database. Add an Or is null condition if you want those too.

Text operators treat every character literally: searching for 50% or a_b finds exactly that text, not a pattern.

Empty values: = null works the same as is null, and != null the same as is not null.

Database differences

• MongoDB: is null also matches documents that don't have the field at all. Use exists / not exists to tell the two apart.
• MongoDB: in compares values exactly as typed, so the text "7" does not match the number 7. Pass numbers from an expression (js:[7, 10]) when the field holds numbers. between always compares numbers as numbers.
• MongoDB: text operators only match fields that hold text.
• MySQL: whether text matching ignores upper and lower case depends on the column's collation. The default one does. Fields inside JSON always ignore case.

Groups (brackets)

Conditions combine strictly left to right: each one joins everything before it with its AND / OR. There is no "AND before OR" rule, so a OR b AND c means (a OR b) AND c.

To put brackets somewhere else, use Add Group. A group's conditions combine first, and then the group joins the list like a single condition.

You want	Build it as
status = active AND (role = admin OR role = owner)	status = active, then Add And Group with role = admin OR role = owner
(age < 18 OR age > 65) AND city = Paris	a group with age < 18 OR age > 65, then Add And Condition city = Paris

• Open a group to edit it. The breadcrumb at the top shows how deep you are; click any part of it to go back up.
• Groups can hold groups, with no depth limit.
• From above, a group shows a one-line summary and how many of its conditions are still empty.
• A group works the same way in DB Get Single, DB Update and DB Delete.
• Optional filters work inside groups: a group whose conditions are all skipped is skipped too, and so is an empty group.

Optional filters

A condition is skipped when its value is undefined when the block runs. This lets one block serve both "filter" and "don't filter" without any branching.

Example: a condition status = js:getQueryParam('status').

Request	What runs
/users?status=active	only records with status = active
/users	every record — the condition is left out

null is not skipped: it is a real value, so a condition with a null value still filters.

Update and Delete

The same rule applies to DB Update and DB Delete. If every condition is skipped (including every condition inside groups), the block updates or deletes every record in the table. Make sure at least one condition always has a value.

Filtering nested / JSON fields

If a column stores JSON data (for example a Postgres jsonb column or a MongoDB document field), you can filter and sort on the values inside it using plain JavaScript-style access:

• Use a dot to reach into a key: attributes.age
• Use brackets to reach into a list: tags[0], items[0].name

Example: a condition on attributes.age with operator >= and value 18 returns only records where the age field inside attributes is 18 or higher. This works the same way whether the value is stored as a number or as a numeric-looking string.

The value side of a condition can also point at a field instead of a fixed value — for example, checking that attributes.age is greater than or equal to attributes.minAge compares two fields on the same record. This has to be marked explicitly as a field reference; otherwise the value is always compared as-is, so an ordinary value that happens to contain dots (an email address, a version number, a domain) is matched exactly and never mistaken for a field name.

MongoDB

Comparing two fields against each other is only available on SQL databases.

Custom conditions

When the built-in operators are not enough — JSON or array operators, regular expressions, full-text search — pick the Custom operator and write the condition yourself. The editor follows your connection's database.

SQL databases (PostgreSQL, MySQL)

Write any expression that could appear after WHERE. Put run-time values inside :

tags @> {{ input.tags }}

created_at > NOW() - INTERVAL '7 days' AND total > {{ input.minTotal }}

• Whatever is inside is JavaScript, with the same variables and helpers as any other expression.
• Each value is sent to the database separately from the SQL text, so a value can never change the query. Do not add quotes around .
• If any value is undefined, the whole condition is skipped (see Optional filters).
• The text is used exactly as written, so it must be valid for your database (for example ILIKE exists in PostgreSQL but not MySQL).

MongoDB

Write JavaScript that returns a MongoDB query filter object — the same object you would pass to find():

return { tags: { $all: input.tags } };

return { $expr: { $gt: ["$spent", "$budget"] } };

• Returning undefined skips the condition.
• The filter is used as-is: field names are the real document fields (_id, not id), and ids must be real ObjectId values.
• See the MongoDB guides on query filters and query operators for everything a filter can do.

Custom conditions combine with the other conditions using And / Or, just like any other row.

Related blocks

• DB Get All, DB Get Single and DB Count: read records.
• DB Update and DB Delete: change or remove records.
• DB Joins: filter across related tables.
• If Condition: the same idea for choosing a path instead of records.