Spaltenorientiertes

Spaltenorientiertes, often translated as columnar or column-oriented, refers to a data storage and processing paradigm fundamentally different from traditional row-oriented systems. In a spaltenorientiertes database, data is physically stored and organized by columns rather than by rows. This means all the values for a particular column are stored contiguously on disk, followed by all the values for the next column, and so on.

This storage structure offers significant advantages for analytical workloads, particularly those involving large datasets and queries that aggregate or analyze specific columns. When a query needs to access only a subset of columns, a spaltenorientiertes system only needs to read the data for those specific columns, drastically reducing disk I/O compared to row-oriented systems, which would have to read entire rows even if only a few values are needed. This leads to much faster query performance for analytical tasks.

Furthermore, spaltenorientiertes storage is highly efficient for data compression. Since all values within a column are typically of the same data type and often share similar patterns, they can be compressed very effectively using techniques like run-length encoding or dictionary encoding. This not only reduces storage space but also further improves query performance by decreasing the amount of data that needs to be read from disk.

While highly beneficial for analytics, spaltenorientiertes databases are generally less performant for transactional workloads that involve frequent updates or insertions of entire rows, as modifying a single row can involve updating multiple distinct storage locations. Therefore, they are best suited for data warehousing, business intelligence, and large-scale data analytics.