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A matrix that has been compressed to eliminate zero-values is a sparse matrix, whereas a matrix with zero and nonzero values is a dense matrix.
Dense indices are faster in general, but sparse indices require less space and impose less maintenance for insertions and deletions.
A dense index in databases is a file with pairs of keys and pointers for every record in the data file. Every key in this file is associated with a particular pointer to a record in the sorted data file. In clustered indices with duplicate keys, the dense index points to the first record with that key.
Sparse indexing has two advantages. The primary one is that it reduces the size of the index, saving space and decreasing maintenance of the index. By decreasing the size of the index, performance is improved. The second advantage is that you do not need to generate unnecessary index entries.
As described in this link
Dense Index:
- An index record appears for every search key value in file.
- This record contains search key value and a pointer to the actual record.
Sparse Index:
- Index records are created only for some of the records.
- To locate a record, we find the index record with the largest search key value less than or equal to the search key value we are looking for.
- We start at that record pointed to by the index record, and proceed along the pointers in the file (that is, sequentially) until we find the desired record.
Also, dense indices are faster in general, but sparse indices require less space and impose less maintenance for insertions and deletions
In Dense Index, an index entry appears for every search-key whereas for Sparse index, an index entry appears for only some of the search-key values.
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