diff --git a/src/main/kotlin/kestrel/store/sql/DiskExecutor.kt b/src/main/kotlin/kestrel/store/sql/DiskExecutor.kt
index cdc7a6c..da057d6 100644
--- a/src/main/kotlin/kestrel/store/sql/DiskExecutor.kt
+++ b/src/main/kotlin/kestrel/store/sql/DiskExecutor.kt
@@ -2573,3 +2573,165 @@ class DiskExecutor(private val catalog: DiskCatalog) : SequenceAccess {
         return scope
     }
 
+    private data class RecursiveCtePlan(val base: QueryStatement, val operator: SetOperator, val recursiveTerm: QueryStatement)
+
+    /**
+     * Recognizes `base UNION [ALL] recursiveTerm` where exactly one side names [cte] in its own
+     * FROM/JOIN - structurally, on the AST, without running anything - mirroring
+     * [kestrel.engine.SelectRunner.splitRecursiveCte] 1:1. Both sides referencing it, or neither,
+     * are rejected/treated as a plain (non-recursive) compound respectively, exactly like the
+     * in-memory engine.
+     */
+    private fun splitRecursiveCte(cte: CommonTableExpression): RecursiveCtePlan? {
+        val query = cte.query
+        if (query !is SetOperationStatement) return null
+        if (query.operator != SetOperator.Union && query.operator != SetOperator.UnionAll) return null
+        val leftRefs = referencesName(query.left, cte.name)
+        val rightRefs = referencesName(query.right, cte.name)
+        return when {
+            leftRefs && rightRefs ->
+                throw DiskExecutorException(
+                    "recursive common table expression '${cte.name}' must not reference itself on both sides of ${query.operator}"
+                )
+            rightRefs -> RecursiveCtePlan(query.left, query.operator, query.right)
+            leftRefs -> RecursiveCtePlan(query.right, query.operator, query.left)
+            else -> null
+        }
+    }
+
+    private fun referencesName(query: QueryStatement, name: String): Boolean = when (query) {
+        is SelectStatement -> referencesName(query.from, name) || query.joins.any { referencesName(it.from, name) }
+        is SetOperationStatement -> referencesName(query.left, name) || referencesName(query.right, name)
+        is WithQuery -> query.ctes.none { it.name.equals(name, ignoreCase = true) } && referencesName(query.body, name)
+    }
+
+    private fun referencesName(item: FromItem, name: String): Boolean = when (item) {
+        is TableSource -> item.name.equals(name, ignoreCase = true)
+        is SubquerySource -> referencesName(item.select, name)
+    }
+
+    private fun cteSchema(cte: CommonTableExpression, result: SelectResult): TableSchema {
+        val labels = cte.columns ?: result.columns
+        if (labels.size != result.columns.size) {
+            throw DiskExecutorException(
+                "common table expression '${cte.name}' expects ${labels.size} columns but its query produces ${result.columns.size}"
+            )
+        }
+        return derivedSchema(cte.name, result, labels)
+    }
+
+    /**
+     * A synthetic schema for a CTE's materialized rows: same idea as
+     * [kestrel.engine.SelectRunner.derivedSchema] - each column's type is inferred from the first
+     * non-NULL value seen in it (defaulting to TEXT when every row is NULL there), since a CTE has
+     * no backing [TableSchema] of its own to borrow one from.
+     */
+    private fun derivedSchema(name: String, result: SelectResult, labels: List<String> = result.columns): TableSchema {
+        val columns = labels.mapIndexed { index, columnName ->
+            val type = result.rows.asSequence().map { it[index] }.firstOrNull { !it.isNull }?.type ?: ColumnType.Text
+            Column(columnName, type, notNull = false, primaryKey = false)
+        }
+        return TableSchema(name, columns)
+    }
+
+    private class CteScope(val name: String, val schema: TableSchema, var rows: List<List<Value>>)
+
+    /** One FROM/JOIN source's row supply: either a real disk table or a CTE's already-materialized rows. */
+    private sealed interface DiskFromSource {
+        val schema: TableSchema
+        fun scan(txn: Long): List<List<Value>>
+    }
+
+    private class DiskTableSource(val table: DiskTable) : DiskFromSource {
+        override val schema get() = table.schema
+        override fun scan(txn: Long): List<List<Value>> = table.scan(txn).map { it.second.values }
+    }
+
+    private class CteRowSource(override val schema: TableSchema, val rows: List<List<Value>>) : DiskFromSource {
+        override fun scan(txn: Long): List<List<Value>> = rows
+    }
+
+    /**
+     * Resolves one FROM/JOIN [name] to its row supply: an active CTE shadows a same-named real
+     * table or view (checked innermost-first via [MutableList.lastOrNull], exactly like
+     * [kestrel.engine.SelectRunner.resolveNamedSource]'s own CTE lookup), then a temp table, then a
+     * real disk table, and only then a view - materialized fresh by running its defining query
+     * inside the same [txn], with [expandingViews] guarding against a view (directly or
+     * transitively) referencing itself, mirroring [kestrel.engine.SelectRunner.resolveNamedSource]
+     * exactly. A temp table's current rows are captured into a [CteRowSource] snapshot exactly like
+     * a CTE's or view's - a plain SELECT never mutates its own FROM source mid-query, so this is
+     * exactly as fresh as scanning a live [DiskTable] would be, and it is what gives a temp table
+     * full JOIN/subquery/aggregate participation for free instead of needing its own parallel query
+     * pipeline. A name that is neither falls through to [DiskCatalog.table], solely for its
+     * "no such table" [DiskCatalogException] - already confirmed absent from
+     * [DiskCatalog.temporaryTableOrNull]/[DiskCatalog.tableOrNull]/[DiskCatalog.viewOrNull], so this
+     * always throws, preserving the exact exception type callers relied on before views existed.
+     */
+    private fun resolveFromSource(name: String, txn: Long): DiskFromSource {
+        activeCtes.lastOrNull { it.name.equals(name, ignoreCase = true) }?.let { return CteRowSource(it.schema, it.rows) }
+        catalog.temporaryTableOrNull(name)?.let { return CteRowSource(it.schema, it.rows.map { row -> row.values }) }
+        catalog.tableOrNull(name)?.let { return DiskTableSource(it) }
+        val view = catalog.viewOrNull(name) ?: return DiskTableSource(catalog.table(name))
+        val key = name.lowercase()
+        if (!expandingViews.add(key)) {
+            throw DiskExecutorException("recursive view definition: $name")
+        }
+        try {
+            val result = runQuery(view, txn, outer = null)
+            return CteRowSource(derivedSchema(name, result), result.rows)
+        } finally {
+            expandingViews.remove(key)
+        }
+    }
+
+    /**
+     * Resolves one FROM/JOIN [item] to its row supply, mirroring
+     * [kestrel.engine.SelectRunner.resolveSource]/`buildSources`: a [TableSource] falls through to
+     * [resolveFromSource] by name (CTE/table/view, unchanged); a non-LATERAL [SubquerySource] (a
+     * derived table) runs its query eagerly, right here, inside the same [txn] - it cannot correlate
+     * to anything, so its rows are fixed for the whole statement, exactly like a materialized view. A
+     * LATERAL [SubquerySource] is different: its rows depend on whichever row of an earlier FROM/JOIN
+     * source it correlates with, which does not exist yet at this point - only its column *names* are
+     * needed here (via [lateralSchema], computed structurally from the AST without running anything)
+     * for offset bookkeeping; its real rows are produced later, per left row, in [executeLateralJoin].
+     */
+    private fun resolveFromItem(item: FromItem, txn: Long): DiskFromSource = when (item) {
+        is TableSource -> resolveFromSource(item.name, txn)
+        is SubquerySource ->
+            if (item.lateral) {
+                CteRowSource(lateralSchema(item), emptyList())
+            } else {
+                val result = runQuery(item.select, txn, outer = null)
+                CteRowSource(derivedSchema(item.alias, result), result.rows)
+            }
+    }
+
+    private fun lateralSchema(item: SubquerySource): TableSchema {
+        val labels = structuralColumnNames(item.select)
+        val columns = labels.map { Column(it, ColumnType.Text, notNull = false, primaryKey = false) }
+        return TableSchema(item.alias, columns)
+    }
+
+    /**
+     * The output column names of [query], derived purely from its AST (no execution, no catalog row
+     * data) - needed to give a LATERAL derived table a stable schema before any row of the source it
+     * correlates with is known. Mirrors [kestrel.engine.SelectRunner.structuralColumnNames] 1:1.
+     */
+    private fun structuralColumnNames(query: QueryStatement, localCtes: Map<String, List<String>> = emptyMap()): List<String> =
+        when (query) {
+            is SelectStatement -> when (val projection = query.projection) {
+                is StarProjection ->
+                    structuralSourceColumnNames(query.from, localCtes) +
+                        query.joins.flatMap { structuralSourceColumnNames(it.from, localCtes) }
+                is ExpressionProjection -> projection.items.mapIndexed { index, item -> columnLabel(item, index) }
+            }
+            is SetOperationStatement -> structuralColumnNames(query.left, localCtes)
+            is WithQuery -> {
+                val extended = localCtes.toMutableMap()
+                for (cte in query.ctes) {
+                    extended[cte.name.lowercase()] = cte.columns ?: structuralColumnNames(cte.query, extended)
+                }
+                structuralColumnNames(query.body, extended)
+            }
+        }
+