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Commit cef7452

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Update docs and whats-new for new vector module enhancements
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‎documentation/src/main/asciidoc/userguide/chapters/query/extensions/Vector.adoc

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@@ -18,8 +18,14 @@ Currently, the following databases are supported:
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* https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/overview-node.html[Oracle database 23ai+]
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* https://mariadb.com/docs/server/reference/sql-structure/vectors/vector-overview[MariaDB 11.7+]
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* https://dev.mysql.com/doc/refman/9.4/en/vector-functions.html[MySQL 9.0+]
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* https://www.cockroachlabs.com/docs/stable/vector[CockroachDB 24.2+]
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* https://www.ibm.com/docs/en/db2/12.1.0?topic=list-vector-values[DB2 12.1+]
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* https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-vector-engine-guide/sap-hana-cloud-sap-hana-database-vector-engine-guide[SAP HANA Cloud QRC 4/2024+]
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* https://learn.microsoft.com/en-us/sql/t-sql/data-types/vector-data-type?view=sql-server-ver17[SQL Server 2025+]
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In theory, the vector-specific functions could be implemented to work with every database that supports arrays.
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Since the performance strongly depends on the existence of a vector index and the search is potentially probabilistic,
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no emulation has been implemented yet.
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[WARNING]
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====
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|===
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| Function | Purpose
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| `cosine_distance()` | Computes the https://en.wikipedia.org/wiki/Cosine_similarity[cosine distance] between two vectors. Maps to the `<``=``>` operator for `pgvector` and maps to the `vector_distance(v1, v2, COSINE)` function for `Oracle AI Vector Search`.
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| `cosine_distance()` | Computes the https://en.wikipedia.org/wiki/Cosine_similarity[cosine distance] between two vectors.
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| `euclidean_distance()` | Computes the https://en.wikipedia.org/wiki/Euclidean_distance[euclidean distance] between two vectors. Maps to the `<``-``>` operator for `pgvector` and maps to the
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`vector_distance(v1, v2, EUCLIDEAN)` function for `Oracle AI Vector Search`.
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| `euclidean_distance()` | Computes the https://en.wikipedia.org/wiki/Euclidean_distance[euclidean distance] between two vectors.
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| `euclidean_squared_distance()` | Computes the https://en.wikipedia.org/wiki/Euclidean_distance#Squared_Euclidean_distance[squared euclidean distance] between two vectors.
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| `l2_distance()` | Alias for `euclidean_distance()`
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| `l2_distance()` | Alias for `euclidean_distance()`.
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| `l2_squared_distance()` | Alias for `euclidean_squared_distance()`
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| `l2_squared_distance()` | Alias for `euclidean_squared_distance()`.
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| `taxicab_distance()` | Computes the https://en.wikipedia.org/wiki/Taxicab_geometry[taxicab distance] between two vectors. Maps to `vector_distance(v1, v2, MANHATTAN)` function for `Oracle AI Vector Search`.
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| `taxicab_distance()` | Computes the https://en.wikipedia.org/wiki/Taxicab_geometry[taxicab distance] between two vectors.
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| `l1_distance()` | Alias for `taxicab_distance()`
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| `l1_distance()` | Alias for `taxicab_distance()`.
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| `hamming_distance()` | Computes the https://en.wikipedia.org/wiki/Hamming_distance[hamming distance] between two vectors. Maps to `vector_distance(v1, v2, HAMMING)` function for `Oracle AI Vector Search`.
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| `hamming_distance()` | Computes the https://en.wikipedia.org/wiki/Hamming_distance[hamming distance] between two vectors.
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| `jaccard_distance()` | Computes the https://en.wikipedia.org/wiki/Jaccard_index[jaccard distance] between two vectors. Maps to the `<``%``>` operator for `pgvector` and maps to the
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`vector_distance(v1, v2, JACCARD)` function for `Oracle AI Vector Search`.
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| `jaccard_distance()` | Computes the https://en.wikipedia.org/wiki/Jaccard_index[jaccard distance] between two vectors.
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| `inner_product()` | Computes the https://en.wikipedia.org/wiki/Inner_product_space[inner product] between two vectors
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| `inner_product()` | Computes the https://en.wikipedia.org/wiki/Inner_product_space[inner product] between two vectors.
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| `negative_inner_product()` | Computes the negative inner product. Maps to the `<``#``>` operator for `pgvector` and maps to the
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`vector_distance(v1, v2, DOT)` function for `Oracle AI Vector Search`.
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| `negative_inner_product()` | Computes the negative inner product.
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| `vector_dims()` | Determines the dimensions of a vector
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| `vector_dims()` | Determines the dimensions of a vector.
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| `vector_norm()` | Computes the https://en.wikipedia.org/wiki/Euclidean_space#Euclidean_norm[Euclidean norm] of a vector
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| `vector_norm()` | Computes the https://en.wikipedia.org/wiki/Euclidean_space#Euclidean_norm[Euclidean norm] of a vector.
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| `l2_norm()` | Alias for `vector_norm()`
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| `l2_norm()` | Alias for `vector_norm()`.
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| `l2_normalize()` | Normalizes each component of a vector by dividing it with the https://en.wikipedia.org/wiki/Euclidean_space#Euclidean_norm[Euclidean norm] of the vector.
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| `binary_quantize()` | Reduces a vector of size N to a binary vector with N bits, using 0 for values <= 0 and 1 for values > 0.
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| `binary_quantize()` | Reduces a vector of size N to a binary vector with N bits, using 0 for values \<= 0 and 1 for values > 0.
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| `subvector()` | Creates a subvector from a given vector, a 1-based start index and a count.
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|===
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===== `taxicab_distance()` and `l1_distance()`
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Computes the https://en.wikipedia.org/wiki/Taxicab_geometry[taxicab distance] between two vectors,
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which is `vector_norm(v1) - vector_norm(v2)`.
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which is `vector_norm(v1) - vector_norm(v2)`. Maps to the `<``+``>` pgvector operator.
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The `l1_distance()` function is an alias.
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[[vector-module-functions-taxicab-distance-example]]
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====
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[[vector-module-functions-subvector]]
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===== `binary_quantize()`
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===== `subvector()`
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Creates a subvector from a given vector, a 1-based start index and a count.
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‎hibernate-core/src/main/java/org/hibernate/type/SqlTypes.java

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* A type code representing a bit precision vector type for databases
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* like {@link org.hibernate.dialect.PostgreSQLDialect PostgreSQL} and
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* {@link org.hibernate.dialect.OracleDialect Oracle 23ai}.
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* @since 7.2
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*/
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public static final int VECTOR_BINARY = 10_004;
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/**
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* A type code representing a half-precision floating-point vector type for databases
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* like {@link org.hibernate.dialect.PostgreSQLDialect PostgreSQL}.
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* @since 7.2
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*/
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public static final int VECTOR_FLOAT16 = 10_005;
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/**
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* A type code representing a sparse single-byte integer vector type for Oracle 23ai database.
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* @since 7.2
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*/
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public static final int SPARSE_VECTOR_INT8 = 10_006;
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/**
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* A type code representing a sparse single-precision floating-point vector type for Oracle 23ai database.
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* @since 7.2
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*/
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public static final int SPARSE_VECTOR_FLOAT32 = 10_007;
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/**
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* A type code representing a sparse double-precision floating-point vector type for Oracle 23ai database.
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* @since 7.2
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*/
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public static final int SPARSE_VECTOR_FLOAT64 = 10_008;
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‎hibernate-vector/src/main/java/org/hibernate/vector/AbstractSparseVector.java

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/**
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* Base class for sparse vectors.
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*
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* @since 7.1
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* @since 7.2
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*/
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public abstract class AbstractSparseVector<E> extends AbstractList<E> {
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‎hibernate-vector/src/main/java/org/hibernate/vector/SparseByteVector.java

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/**
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* {@link java.util.List} implementation for a sparse byte vector.
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*
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* @since 7.1
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* @since 7.2
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*/
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public class SparseByteVector extends AbstractSparseVector<Byte> {
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‎hibernate-vector/src/main/java/org/hibernate/vector/SparseDoubleVector.java

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/**
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* {@link List} implementation for a sparse byte vector.
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*
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* @since 7.1
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* @since 7.2
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*/
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public class SparseDoubleVector extends AbstractSparseVector<Double> {
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‎hibernate-vector/src/main/java/org/hibernate/vector/SparseFloatVector.java

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/**
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* {@link List} implementation for a sparse byte vector.
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*
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* @since 7.1
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* @since 7.2
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*/
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public class SparseFloatVector extends AbstractSparseVector<Float> {
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‎hibernate-vector/src/main/java/org/hibernate/vector/internal/VectorDdlType.java

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/**
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* DDL type for vector types.
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*
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* @since 7.1
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* @since 7.2
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*/
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public class VectorDdlType extends DdlTypeImpl {
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‎hibernate-vector/src/main/java/org/hibernate/vector/internal/VectorHelper.java

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/**
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* Helper for vector related functionality.
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*
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* @since 7.1
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* @since 7.2
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*/
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public class VectorHelper {
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‎whats-new.adoc

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IMPORTANT: If migrating from earlier versions, be sure to also check out the link:{migrationGuide}[Migration Guide] for discussion of impactful changes.
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[[vector-module-enhancements]]
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== Hibernate-Vector module enhancements
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Support for binary, float16 and sparse vectors were added.
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====
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[source, java, indent=0]
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----
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@Entity
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public class MyEntity {
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@Id
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UUID id;
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@JdbcTypeCode(SqlTypes.VECTOR_BINARY)
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@Array(length = 24) // Refers to the bit count
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byte[] binaryVector;
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@JdbcTypeCode(SqlTypes.VECTOR_FLOAT16)
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@Array(length = 3)
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float[] float16Vector;
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@Array(length = 3)
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SparseFloatVector sparseFloat32Vector;
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}
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----
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====
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The Hibernate Vector module currently ships with 3 sparse vector types:
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* `SparseByteVector`
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* `SparseFloatVector`
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* `SparseDoubleVector`
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In addition to accessing the sparse indices and values, they also implement the `List` interface to provide access
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as if it were a dense vector.
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Also, support for vectors in the following databases was added:
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* https://dev.mysql.com/doc/refman/9.4/en/vector-functions.html[MySQL 9.0+]
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* https://www.ibm.com/docs/en/db2/12.1.0?topic=list-vector-values[DB2 12.1+]
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* https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-vector-engine-guide/sap-hana-cloud-sap-hana-database-vector-engine-guide[SAP HANA Cloud QRC 4/2024+]
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* https://learn.microsoft.com/en-us/sql/t-sql/data-types/vector-data-type?view=sql-server-ver17[SQL Server 2025+]

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