What are the different data compression techniques used in NoSQL databases?

NoSQL databases employ various data compression techniques to optimize storage and improve performance. Some of the commonly used techniques are:

1. Dictionary Compression: This technique involves creating a dictionary of frequently occurring terms or values in the dataset. Instead of storing the actual values, the dictionary is used to map the values to shorter codes or references, resulting in reduced storage requirements.

2. Run-Length Encoding (RLE): RLE is a simple compression technique that replaces consecutive repeated values with a count and a single instance of the value. It is particularly effective for compressing datasets with long sequences of repeated values.

3. Delta Encoding: Delta encoding involves storing the difference between consecutive values instead of the actual values themselves. This technique is useful for compressing datasets with a high degree of similarity between adjacent values.

4. Bit Packing: Bit packing is a compression technique that aims to reduce the storage space required for storing boolean or integer values. It involves packing multiple values into a single machine word or byte, thereby reducing the overall storage requirements.

5. Huffman Coding: Huffman coding is a widely used compression technique that assigns variable-length codes to different values based on their frequency of occurrence. Values that occur more frequently are assigned shorter codes, resulting in efficient storage.

6. Lempel-Ziv-Welch (LZW) Compression: LZW compression is a dictionary-based compression technique that replaces frequently occurring patterns or sequences of characters with shorter codes. It is commonly used for compressing text-based data in NoSQL databases.

7. Columnar Compression: Columnar compression is a technique specifically designed for columnar databases, where data is stored and processed column-wise instead of row-wise. It involves compressing each column independently using techniques like dictionary encoding, run-length encoding, or bit packing, resulting in significant storage savings.

It is important to note that the choice of compression technique depends on the specific characteristics of the dataset and the requirements of the application. NoSQL databases often employ a combination of these techniques to achieve optimal compression and performance.