diff --git a/cpp/include/raft/neighbors/cagra_types.hpp b/cpp/include/raft/neighbors/cagra_types.hpp
index 7eb5e21f53..34e79987ae 100644
--- a/cpp/include/raft/neighbors/cagra_types.hpp
+++ b/cpp/include/raft/neighbors/cagra_types.hpp
@@ -256,7 +256,7 @@ struct index : ann::index {
         mdspan<const IdxT, matrix_extent<int64_t>, row_major, graph_accessor> knn_graph)
     : ann::index(),
       metric_(metric),
-      dataset_(construct_aligned_dataset(res, dataset, uint32_t{16})),
+      dataset_(upcast_dataset_ptr(construct_aligned_dataset(res, dataset, 16))),
       graph_(make_device_matrix<IdxT, int64_t>(res, 0, 0))
   {
     RAFT_EXPECTS(dataset.extent(0) == knn_graph.extent(0),
@@ -275,14 +275,14 @@ struct index : ann::index {
   void update_dataset(raft::resources const& res,
                       raft::device_matrix_view<const T, int64_t, row_major> dataset)
   {
-    construct_aligned_dataset(res, dataset, 16).swap(dataset_);
+    upcast_dataset_ptr(construct_aligned_dataset(res, dataset, 16)).swap(dataset_);
   }
 
   /** Set the dataset reference explicitly to a device matrix view with padding. */
   void update_dataset(raft::resources const& res,
                       raft::device_matrix_view<const T, int64_t, layout_stride> dataset)
   {
-    construct_aligned_dataset(res, dataset, 16).swap(dataset_);
+    upcast_dataset_ptr(construct_aligned_dataset(res, dataset, 16)).swap(dataset_);
   }
 
   /**
@@ -293,7 +293,15 @@ struct index : ann::index {
   void update_dataset(raft::resources const& res,
                       raft::host_matrix_view<const T, int64_t, row_major> dataset)
   {
-    construct_aligned_dataset(res, dataset, 16).swap(dataset_);
+    upcast_dataset_ptr(construct_aligned_dataset(res, dataset, 16)).swap(dataset_);
+  }
+
+  /** Replace the dataset with a new dataset. */
+  template <typename DatasetT>
+  auto update_dataset(raft::resources const& res, DatasetT&& dataset)
+    -> std::enable_if_t<std::is_base_of_v<neighbors::dataset<int64_t>, DatasetT>>
+  {
+    upcast_dataset_ptr(std::make_unique<DatasetT>(std::move(dataset))).swap(dataset_);
   }
 
   /**
diff --git a/cpp/include/raft/neighbors/dataset.hpp b/cpp/include/raft/neighbors/dataset.hpp
index cc655438bc..8586757679 100644
--- a/cpp/include/raft/neighbors/dataset.hpp
+++ b/cpp/include/raft/neighbors/dataset.hpp
@@ -34,28 +34,32 @@ namespace raft::neighbors {
 /** Two-dimensional dataset; maybe owning, maybe compressed, maybe strided. */
 template <typename IdxT>
 struct dataset {
+  using index_type = IdxT;
   /**  Size of the dataset. */
-  [[nodiscard]] virtual auto n_rows() const noexcept -> IdxT;
+  [[nodiscard]] virtual auto n_rows() const noexcept -> index_type = 0;
   /** Dimensionality of the dataset. */
-  [[nodiscard]] virtual auto dim() const noexcept -> uint32_t;
+  [[nodiscard]] virtual auto dim() const noexcept -> uint32_t = 0;
   /** Whether the object owns the data. */
-  [[nodiscard]] virtual auto is_owning() const noexcept -> bool;
-  virtual ~dataset() noexcept = default;
+  [[nodiscard]] virtual auto is_owning() const noexcept -> bool = 0;
+  virtual ~dataset() noexcept                                   = default;
 };
 
 template <typename IdxT>
 struct empty_dataset : public dataset<IdxT> {
+  using index_type = IdxT;
   uint32_t suggested_dim;
   explicit empty_dataset(uint32_t dim) noexcept : suggested_dim(0) {}
-  [[nodiscard]] auto n_rows() const noexcept -> IdxT final { return 0; }
+  [[nodiscard]] auto n_rows() const noexcept -> index_type final { return 0; }
   [[nodiscard]] auto dim() const noexcept -> uint32_t final { return suggested_dim; }
   [[nodiscard]] auto is_owning() const noexcept -> bool final { return true; }
 };
 
 template <typename DataT, typename IdxT>
 struct strided_dataset : public dataset<IdxT> {
-  using view_type = device_matrix_view<const DataT, IdxT, layout_stride>;
-  [[nodiscard]] auto n_rows() const noexcept -> IdxT final { return view().extent(0); }
+  using index_type = IdxT;
+  using value_type = DataT;
+  using view_type  = device_matrix_view<const value_type, index_type, layout_stride>;
+  [[nodiscard]] auto n_rows() const noexcept -> index_type final { return view().extent(0); }
   [[nodiscard]] auto dim() const noexcept -> uint32_t final
   {
     return static_cast<uint32_t>(view().extent(1));
@@ -71,7 +75,9 @@ struct strided_dataset : public dataset<IdxT> {
 
 template <typename DataT, typename IdxT>
 struct non_owning_dataset : public strided_dataset<DataT, IdxT> {
-  using typename strided_dataset<DataT, IdxT>::view_type;
+  using index_type = IdxT;
+  using value_type = DataT;
+  using typename strided_dataset<value_type, index_type>::view_type;
   view_type data;
   explicit non_owning_dataset(view_type data) noexcept : data(data) {}
   [[nodiscard]] auto is_owning() const noexcept -> bool final { return false; }
@@ -80,8 +86,11 @@ struct non_owning_dataset : public strided_dataset<DataT, IdxT> {
 
 template <typename DataT, typename IdxT, typename LayoutPolicy, typename ContainerPolicy>
 struct owning_dataset : public strided_dataset<DataT, IdxT> {
-  using typename strided_dataset<DataT, IdxT>::view_type;
-  using storage_type = mdarray<DataT, matrix_extent<IdxT>, LayoutPolicy, ContainerPolicy>;
+  using index_type = IdxT;
+  using value_type = DataT;
+  using typename strided_dataset<value_type, index_type>::view_type;
+  using storage_type =
+    mdarray<value_type, matrix_extent<index_type>, LayoutPolicy, ContainerPolicy>;
   using mapping_type = typename view_type::mapping_type;
   storage_type data;
   mapping_type view_mapping;
@@ -153,17 +162,26 @@ auto construct_strided_dataset(const raft::resources& res,
 
 template <typename SrcT>
 auto construct_aligned_dataset(const raft::resources& res, const SrcT& src, uint32_t align_bytes)
-  -> std::unique_ptr<dataset<typename SrcT::index_type>>
+  -> std::unique_ptr<strided_dataset<typename SrcT::value_type, typename SrcT::index_type>>
 {
   using value_type       = typename SrcT::value_type;
   using index_type       = typename SrcT::index_type;
-  using out_type         = dataset<index_type>;
+  using out_type         = strided_dataset<value_type, index_type>;
   constexpr size_t kSize = sizeof(value_type);
   uint32_t required_stride =
     raft::round_up_safe<size_t>(src.extent(1) * kSize, align_bytes) / kSize;
   return std::unique_ptr<out_type>{construct_strided_dataset(res, src, required_stride).release()};
 }
 
+template <typename DatasetT>
+auto upcast_dataset_ptr(std::unique_ptr<DatasetT>&& src)
+  -> std::unique_ptr<dataset<typename DatasetT::index_type>>
+{
+  using out_type = dataset<typename DatasetT::index_type>;
+  static_assert(std::is_base_of_v<out_type, DatasetT>, "The source must be a child of `dataset`");
+  return std::unique_ptr<out_type>{src.release()};
+}
+
 /** Parameters for VPQ compression. */
 struct vpq_params {
   /**
diff --git a/cpp/include/raft/neighbors/detail/cagra/cagra_build.cuh b/cpp/include/raft/neighbors/detail/cagra/cagra_build.cuh
index 08cc2beaeb..743188dae3 100644
--- a/cpp/include/raft/neighbors/detail/cagra/cagra_build.cuh
+++ b/cpp/include/raft/neighbors/detail/cagra/cagra_build.cuh
@@ -16,6 +16,7 @@
 #pragma once
 
 #include "../../cagra_types.hpp"
+#include "../../vpq_dataset.cuh"
 #include "graph_core.cuh"
 
 #include <raft/core/device_mdarray.hpp>
@@ -344,6 +345,16 @@ index<T, IdxT> build(
   RAFT_LOG_INFO("Graph optimized, creating index");
   // Construct an index from dataset and optimized knn graph.
   if (construct_index_with_dataset) {
+    if (params.compression.has_value()) {
+      index<T, IdxT> idx(res, params.metric);
+      idx.update_graph(res, raft::make_const_mdspan(cagra_graph.view()));
+      idx.update_dataset(
+        res,
+        // TODO: ATM, only float math type is supported in kmeans training.
+        //       Later, we can do runtime dispatching of the math type.
+        neighbors::vpq_build<decltype(dataset), float, int64_t>(res, *params.compression, dataset));
+      return idx;
+    }
     return index<T, IdxT>(res, params.metric, dataset, raft::make_const_mdspan(cagra_graph.view()));
   } else {
     // We just add the graph. User is expected to update dataset separately. This branch is used