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Documentation Index

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Run conditions are expressions that Databar evaluates for every row before running an enrichment. If the expression returns true, the row is processed. If it returns false, the row is skipped. This gives you two advantages:
  • Better data quality — only enrich rows that meet your criteria, so you don’t waste processing on irrelevant data.
  • Lower cost — skipped rows do not consume credits.

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Syntax basics

Run conditions use CEL (Common Expression Language), an open expression language created by Google. To reference a column in your table, type { and select the column name. 
{country} == "US" && {employee_count} >= 50
The expression above runs the enrichment only for US-based companies with 50 or more employees.

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Operator reference

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Comparison operators

OperatorMeaningExample
==Equal to{country} == "US"
!=Not equal to{status} != "inactive"
>Greater than{lead_score} > 80
<Less than{employee_count} < 500
>=Greater than or equal{revenue} >= 1000000
<=Less than or equal{founded_year} <= 2010

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Logical operators

OperatorMeaningExample
&&AND — both sides must be true{country} == "US" && {employee_count} >= 50
||OR — at least one side must be true{title} == "CEO" || {title} == "CTO"
!NOT — flips true to false!{website}.contains("test")
( )Group rules together({country} == "US" || {country} == "CA") && {revenue} >= 1000000

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Text operators

OperatorMeaningExample
.contains("x")True if text contains “x”{email}.contains("@gmail.com")
.startsWith("x")True if text starts with “x”{phone}.startsWith("+1")
.endsWith("x")True if text ends with “x”{domain}.endsWith(".io")
.size()Number of characters{email}.size() > 0
.matches("regex")Regex match{email}.matches("^.+@.+\\..+$")
.lowerAscii()Convert to lowercase{country}.lowerAscii() == "us"
.upperAscii()Convert to uppercase{code}.upperAscii() == "USA"
+Join text{first_name} + " " + {last_name}

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Math operators

OperatorMeaning
+Addition
-Subtraction
*Multiplication
/Division
%Modulo (remainder)

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List operators

OperatorMeaningExample
"x" in listTrue if “x” is in the list"VIP" in {tags}
.size()Number of items{tags}.size() > 0
.exists(x, condition)At least one item matches{tags}.exists(t, t.contains("enterprise"))
.all(x, condition)Every item matches{tags}.all(t, t != "")

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Handling empty values

OperatorMeaningExample
has(column)True if the column has a valuehas({email}) && {email}.contains("@gmail.com")
column != ""True if not empty text{email} != ""
Always check for empty values before calling text operators like .contains() or .startsWith(). Calling these on an empty cell can cause unexpected behavior.

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Examples

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Simple conditions (single rule)

GoalExpression
Only Gmail addresses{email}.contains("@gmail.com")
High-scoring leads{lead_score} > 80
US-based companies{country} == "US"
Skip empty emails{email} != ""
VIP-tagged contacts"VIP" in {tags}
Skip test websites!{website}.contains("test")

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Combining two conditions

GoalExpression
US companies with 50+ employees{country} == "US" && {employee_count} >= 50
Active leads with high scores{status} == "active" && {lead_score} > 80
Email present and valid format{email} != "" && {email}.contains("@")
CEOs or CTOs only{title} == "CEO" || {title} == "CTO"
High revenue or Series B funding{revenue} >= 5000000 || {funding_stage} == "Series B"

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Combining three conditions

GoalExpression
C-level execs at large US companies{country} == "US" && {employee_count} >= 500 && {title}.contains("Chief")
US or Canada, 50+ employees({country} == "US" || {country} == "CA") && {employee_count} >= 50
Active enterprise leads with email{status} == "active" && {plan} == "enterprise" && {email} != ""
Skip test, demo, and example domains!{domain}.contains("test") && !{domain}.contains("demo") && !{domain}.contains("example")

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Combining four or more conditions

GoalExpression
Enterprise targets in North America with budget({country} == "US" || {country} == "CA") && {employee_count} >= 200 && {revenue} >= 1000000 && {status} == "active"
Qualified SaaS leads{industry} == "SaaS" && {employee_count} >= 50 && {lead_score} > 70 && has({email})
Senior decision-makers at funded companies({title}.contains("VP") || {title}.contains("Director") || {title}.contains("Chief")) && {funding_stage} != "" && {employee_count} >= 100 && {country} == "US"

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Tips

Before running an enrichment with a new condition across thousands of rows, use the Run single row option or filter your table to a small subset. This lets you verify the condition behaves as expected without spending credits.
When mixing && and ||, wrap groups in parentheses so the evaluation order is clear. Without parentheses, && binds more tightly than ||, which can produce unexpected results.
// Ambiguous
{country} == "US" || {country} == "CA" && {revenue} >= 1000000

// Clear
({country} == "US" || {country} == "CA") && {revenue} >= 1000000
Use has({column}) or {column} != "" before operating on a column that might be empty. This prevents errors from calling .contains() or .startsWith() on a null value.
CEL is type-aware. If a column stores numbers as text, you may need to convert with int() before comparing:
int({employee_count}) >= 50
Similarly, text comparisons are case-sensitive by default. Use .lowerAscii() to normalize.
Rows that fail a run condition are not sent to the data provider and do not consume credits. Use conditions aggressively to keep costs predictable.

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Next steps

Enrichments

Learn how to add and run enrichments on your tables.

Automations

Combine run conditions with scheduled or event-driven automation.