diff --git a/datafusion/physical-plan/src/spill/in_memory_spill_buffer.rs b/datafusion/physical-plan/src/spill/in_memory_spill_buffer.rs
new file mode 100644
index 000000000000..bba0f6f95625
--- /dev/null
+++ b/datafusion/physical-plan/src/spill/in_memory_spill_buffer.rs
@@ -0,0 +1,46 @@
+use crate::memory::MemoryStream;
+use crate::spill::spill_manager::GetSlicedSize;
+use arrow::array::RecordBatch;
+use datafusion_common::Result;
+use datafusion_execution::SendableRecordBatchStream;
+use std::sync::Arc;
+
+#[derive(Debug)]
+pub struct InMemorySpillBuffer {
+    batches: Vec<RecordBatch>,
+    total_bytes: usize,
+}
+
+impl InMemorySpillBuffer {
+    pub fn from_batch(batch: &RecordBatch) -> Result<Self> {
+        Ok(Self {
+            batches: vec![batch.clone()],
+            total_bytes: batch.get_sliced_size()?,
+        })
+    }
+
+    pub fn from_batches(batches: &[RecordBatch]) -> Result<Self> {
+        let mut total_bytes = 0;
+        let mut owned = Vec::with_capacity(batches.len());
+        for b in batches {
+            total_bytes += b.get_sliced_size()?;
+            owned.push(b.clone());
+        }
+        Ok(Self {
+            batches: owned,
+            total_bytes,
+        })
+    }
+
+    pub fn as_stream(
+        self: Arc<Self>,
+        schema: Arc<arrow_schema::Schema>,
+    ) -> Result<SendableRecordBatchStream> {
+        let stream = MemoryStream::try_new(self.batches.clone(), schema, None)?;
+        Ok(Box::pin(stream))
+    }
+
+    pub fn size(&self) -> usize {
+        self.total_bytes
+    }
+}
diff --git a/datafusion/physical-plan/src/spill/mod.rs b/datafusion/physical-plan/src/spill/mod.rs
index fab62bff840f..270b3654b2ba 100644
--- a/datafusion/physical-plan/src/spill/mod.rs
+++ b/datafusion/physical-plan/src/spill/mod.rs
@@ -19,6 +19,7 @@
 
 pub(crate) mod in_progress_spill_file;
 pub(crate) mod spill_manager;
+pub(crate) mod in_memory_spill_buffer;
 
 use std::fs::File;
 use std::io::BufReader;
@@ -376,17 +377,18 @@ mod tests {
     use crate::common::collect;
     use crate::metrics::ExecutionPlanMetricsSet;
     use crate::metrics::SpillMetrics;
-    use crate::spill::spill_manager::SpillManager;
+    use crate::spill::spill_manager::{SpillLocation, SpillManager};
     use crate::test::build_table_i32;
     use arrow::array::{ArrayRef, Float64Array, Int32Array, ListArray, StringArray};
     use arrow::compute::cast;
     use arrow::datatypes::{DataType, Field, Int32Type, Schema};
     use arrow::record_batch::RecordBatch;
     use datafusion_common::Result;
-    use datafusion_execution::runtime_env::RuntimeEnv;
+    use datafusion_execution::runtime_env::{RuntimeEnv, RuntimeEnvBuilder};
     use futures::StreamExt as _;
 
     use std::sync::Arc;
+    use datafusion_execution::memory_pool::{FairSpillPool, MemoryPool};
 
     #[tokio::test]
     async fn test_batch_spill_and_read() -> Result<()> {
@@ -426,6 +428,65 @@ mod tests {
         Ok(())
     }
 
+    #[tokio::test]
+    async fn test_batch_spill_to_memory_and_disk_and_read() -> Result<()> {
+        let schema: SchemaRef = Arc::new(Schema::new(vec![
+            Field::new("a", DataType::Int32, false),
+            Field::new("b", DataType::Int32, false),
+        ]));
+
+        let batch1 = RecordBatch::try_new(
+            Arc::clone(&schema),
+            vec![
+                Arc::new(Int32Array::from_iter_values(0..1000)),
+                Arc::new(Int32Array::from_iter_values(1000..2000)),
+            ],
+        )?;
+
+        let batch2 = RecordBatch::try_new(
+            Arc::clone(&schema),
+            vec![
+                Arc::new(Int32Array::from_iter_values(2000..4000)),
+                Arc::new(Int32Array::from_iter_values(4000..6000)),
+            ],
+        )?;
+
+        let num_rows = batch1.num_rows() + batch2.num_rows();
+        let batches = vec![batch1, batch2];
+
+        // --- create small memory pool (simulate memory pressure) ---
+        let memory_limit_bytes = 20 * 1024; // 20KB
+        let memory_pool: Arc<dyn MemoryPool> = Arc::new(FairSpillPool::new(memory_limit_bytes));
+
+
+        // Construct SpillManager
+        let env = RuntimeEnvBuilder::new()
+            .with_memory_pool(memory_pool)
+            .build_arc()?;
+        let metrics = SpillMetrics::new(&ExecutionPlanMetricsSet::new(), 0);
+        let spill_manager = SpillManager::new(env, metrics, Arc::clone(&schema));
+
+        let results = spill_manager.spill_batches_auto(&batches, "TestAutoSpill")?;
+        assert_eq!(results.len(), 2);
+
+        let mem_count = results.iter().filter(|r| matches!(r, SpillLocation::Memory(_))).count();
+        let disk_count = results.iter().filter(|r| matches!(r, SpillLocation::Disk(_))).count();
+        assert!(mem_count >= 1);
+        assert!(disk_count >= 1);
+
+        let spilled_rows = spill_manager.metrics.spilled_rows.value();
+        assert_eq!(spilled_rows, num_rows);
+
+        for spill in results {
+            let stream = spill_manager.load_spilled_batch(spill)?;
+            let collected = collect(stream).await?;
+            assert!(!collected.is_empty());
+            assert_eq!(collected[0].schema(), schema);
+        }
+
+        Ok(())
+    }
+
     #[tokio::test]
     async fn test_batch_spill_and_read_dictionary_arrays() -> Result<()> {
         // See https://github.com/apache/datafusion/issues/4658
diff --git a/datafusion/physical-plan/src/spill/spill_manager.rs b/datafusion/physical-plan/src/spill/spill_manager.rs
index ad23bd66a021..e8f5037f764b 100644
--- a/datafusion/physical-plan/src/spill/spill_manager.rs
+++ b/datafusion/physical-plan/src/spill/spill_manager.rs
@@ -21,15 +21,17 @@ use arrow::array::StringViewArray;
 use arrow::datatypes::SchemaRef;
 use arrow::record_batch::RecordBatch;
 use datafusion_execution::runtime_env::RuntimeEnv;
+use std::slice;
 use std::sync::Arc;
 
-use datafusion_common::{config::SpillCompression, Result};
+use datafusion_common::{config::SpillCompression, DataFusionError, Result};
 use datafusion_execution::disk_manager::RefCountedTempFile;
 use datafusion_execution::SendableRecordBatchStream;
 
 use super::{in_progress_spill_file::InProgressSpillFile, SpillReaderStream};
 use crate::coop::cooperative;
 use crate::{common::spawn_buffered, metrics::SpillMetrics};
+use crate::spill::in_memory_spill_buffer::InMemorySpillBuffer;
 
 /// The `SpillManager` is responsible for the following tasks:
 /// - Reading and writing `RecordBatch`es to raw files based on the provided configurations.
@@ -168,6 +170,47 @@ impl SpillManager {
         Ok(file.map(|f| (f, max_record_batch_size)))
     }
 
+    /// Automatically decides whether to spill the given RecordBatch to memory or disk,
+    /// depending on available memory pool capacity.
+    pub(crate) fn spill_batch_auto(&self, batch: &RecordBatch, request_msg: &str) -> Result<SpillLocation> {
+        let size = batch.get_sliced_size()?;
+
+        // Check current memory usage and total limit from the runtime memory pool
+        let used = self.env.memory_pool.reserved();
+        let limit = match self.env.memory_pool.memory_limit() {
+            datafusion_execution::memory_pool::MemoryLimit::Finite(l) => l,
+            _ => usize::MAX,
+        };
+
+        // If there's enough memory (with a small safety margin), keep it in memory
+        if used + size * 3 / 2 <= limit {
+            let buf = Arc::new(InMemorySpillBuffer::from_batch(batch)?);
+            self.metrics.spilled_bytes.add(size);
+            self.metrics.spilled_rows.add(batch.num_rows());
+            Ok(SpillLocation::Memory(buf))
+        } else {
+            // Otherwise spill to disk using the existing SpillManager logic
+            let Some(file) = self.spill_record_batch_and_finish(slice::from_ref(batch), request_msg)? else {
+                return Err(DataFusionError::Execution(
+                    "failed to spill batch to disk".into(),
+                ));
+            };
+            Ok(SpillLocation::Disk(file))
+        }
+    }
+
+    pub fn spill_batches_auto(
+        &self,
+        batches: &[RecordBatch],
+        request_msg: &str,
+    ) -> Result<Vec<SpillLocation>> {
+        let mut result = Vec::with_capacity(batches.len());
+        for batch in batches {
+            result.push(self.spill_batch_auto(batch, request_msg)?);
+        }
+        Ok(result)
+    }
+
     /// Reads a spill file as a stream. The file must be created by the current `SpillManager`.
     /// This method will generate output in FIFO order: the batch appended first
     /// will be read first.
@@ -182,8 +225,25 @@ impl SpillManager {
 
         Ok(spawn_buffered(stream, self.batch_read_buffer_capacity))
     }
+
+    pub fn load_spilled_batch(
+        &self,
+        spill: SpillLocation,
+    ) -> Result<SendableRecordBatchStream> {
+        match spill {
+            SpillLocation::Memory(buf) => Ok(buf.as_stream(Arc::clone(&self.schema))?),
+            SpillLocation::Disk(file) => self.read_spill_as_stream(file),
+        }
+    }
+}
+
+#[derive(Debug)]
+pub enum SpillLocation {
+    Memory(Arc<InMemorySpillBuffer>),
+    Disk(RefCountedTempFile),
 }
 
+
 pub(crate) trait GetSlicedSize {
     /// Returns the size of the `RecordBatch` when sliced.
     /// Note: if multiple arrays or even a single array share the same data buffers, we may double count each buffer.