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diff --git a/subprojects/viatra-runtime-rete/src/main/java/tools/refinery/viatra/runtime/rete/aggregation/timely/FirstOnlySequentialTimelyColumnAggregatorNode.java b/subprojects/viatra-runtime-rete/src/main/java/tools/refinery/viatra/runtime/rete/aggregation/timely/FirstOnlySequentialTimelyColumnAggregatorNode.java
new file mode 100644
index 00000000..79197aac
--- /dev/null
+++ b/subprojects/viatra-runtime-rete/src/main/java/tools/refinery/viatra/runtime/rete/aggregation/timely/FirstOnlySequentialTimelyColumnAggregatorNode.java
@@ -0,0 +1,117 @@
+/*******************************************************************************
+ * Copyright (c) 2010-2019, Tamas Szabo, itemis AG, Gabor Bergmann, IncQuery Labs Ltd.
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License v. 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-v20.html.
+ * 
+ * SPDX-License-Identifier: EPL-2.0
+ *******************************************************************************/
+package tools.refinery.viatra.runtime.rete.aggregation.timely;
+
+import java.util.Objects;
+import java.util.TreeMap;
+
+import tools.refinery.viatra.runtime.matchers.psystem.aggregations.IMultisetAggregationOperator;
+import tools.refinery.viatra.runtime.matchers.tuple.Tuple;
+import tools.refinery.viatra.runtime.matchers.tuple.TupleMask;
+import tools.refinery.viatra.runtime.matchers.util.Direction;
+import tools.refinery.viatra.runtime.rete.network.ReteContainer;
+import tools.refinery.viatra.runtime.rete.network.communication.Timestamp;
+
+/**
+ * First-only column aggregator with sequential aggregation architecture. 
+ * 
+ * @author Tamas Szabo
+ * @since 2.4
+ */
+public class FirstOnlySequentialTimelyColumnAggregatorNode<Domain, Accumulator, AggregateResult>
+        extends FirstOnlyTimelyColumnAggregatorNode<Domain, Accumulator, AggregateResult> {
+
+    public FirstOnlySequentialTimelyColumnAggregatorNode(final ReteContainer reteContainer,
+            final IMultisetAggregationOperator<Domain, Accumulator, AggregateResult> operator,
+            final TupleMask groupMask, final TupleMask columnMask) {
+        super(reteContainer, operator, groupMask, columnMask);
+    }
+
+    /**
+     * Accumulator gets modified only at the timestamp where the update happened. During the folding, accumulators are
+     * never changed at higher timestamps. Aggregate results at higher timestamps may change due to the change at the
+     * input timestamp. Uniqueness enforcement may require from aggregate results to jump up/down on demand during the
+     * folding.
+     */
+    @Override
+    public void update(final Direction direction, final Tuple update, final Timestamp timestamp) {
+        final Tuple group = groupMask.transform(update);
+        final Tuple value = columnMask.transform(update);
+        @SuppressWarnings("unchecked")
+        final Domain aggregand = (Domain) runtimeContext.unwrapElement(value.get(0));
+        final boolean isInsertion = direction == Direction.INSERT;
+
+        final AggregateResult previousResult = getResultRaw(group, timestamp, true);
+
+        final Accumulator oldAccumulator = getAccumulator(group, timestamp);
+        final AggregateResult oldResult = previousResult == null ? operator.getAggregate(oldAccumulator)
+                : operator.combine(previousResult, oldAccumulator);
+
+        final Accumulator newAccumulator = operator.update(oldAccumulator, aggregand, isInsertion);
+        final AggregateResult newResult = previousResult == null ? operator.getAggregate(newAccumulator)
+                : operator.combine(previousResult, newAccumulator);
+
+        storeIfNotNeutral(group, newAccumulator, newResult, timestamp);
+
+        propagateWithChecks(group, timestamp, previousResult, previousResult, oldResult, newResult);
+
+        // fold up the state towards higher timestamps
+        if (!Objects.equals(oldResult, newResult)) {
+            AggregateResult previousOldResult = oldResult;
+            AggregateResult previousNewResult = newResult;
+            AggregateResult currentOldResult = null;
+            AggregateResult currentNewResult = null;
+            final TreeMap<Timestamp, CumulativeAggregate<Accumulator, AggregateResult>> groupEntries = this.memory
+                    .get(group);
+
+            Timestamp currentTimestamp = groupEntries == null ? null : groupEntries.higherKey(timestamp);
+
+            while (currentTimestamp != null) {
+                // they cannot be the same, otherwise we would not even be here
+                assert !Objects.equals(previousOldResult, previousNewResult);
+
+                final Accumulator accumulator = getAccumulator(group, currentTimestamp);
+                currentOldResult = groupEntries.get(currentTimestamp).result;
+                currentNewResult = operator.combine(previousNewResult, accumulator);
+
+                // otherwise we would not be iterating over this timestamp
+                assert !operator.isNeutral(accumulator);
+
+                propagateWithChecks(group, currentTimestamp, previousOldResult, previousNewResult, currentOldResult,
+                        currentNewResult);
+
+                if (!Objects.equals(currentOldResult, currentNewResult)) {
+                    storeIfNotNeutral(group, accumulator, currentNewResult, currentTimestamp);
+                    previousOldResult = currentOldResult;
+                    previousNewResult = currentNewResult;
+                    currentTimestamp = groupEntries.higherKey(currentTimestamp);
+                } else {
+                    // we can stop the folding from here
+                    break;
+                }
+            }
+        }
+    }
+
+    @Override
+    protected Accumulator getAccumulator(final Tuple group, final Timestamp timestamp) {
+        final TreeMap<Timestamp, CumulativeAggregate<Accumulator, AggregateResult>> entryMap = this.memory.get(group);
+        if (entryMap == null) {
+            return operator.createNeutral();
+        } else {
+            final CumulativeAggregate<Accumulator, AggregateResult> entry = entryMap.get(timestamp);
+            if (entry == null) {
+                return operator.createNeutral();
+            } else {
+                return entry.accumulator;
+            }
+        }
+    }
+
+}