Bitfields in Redis

Redis bitfields allow you to set, increase, and get integer values with any number of bits. You can, for instance, work with everything from signed 63-bit numbers to unsigned 1-bit integers.

Basic Commands used in Bitfields in Redis:

  • BITFIELD : This command will atomically sets, increments and reads one or more values.
  • BITFIELD_RO: This command is a read-only variant of BITFIELD.

Complete Guide on Redis Data Types with Commands and Storage

Redis is an open-source, in-memory data store that supports various data types: such as String, Sets, Lists, Hashes, etc. to store data according to the needs of the user. These diverse data types make Redis versatile for caching, messaging, real-time analytics, and more.

Different Data Types in Redis

  • 1. String Data Type in Redis
  • 2. Hash Data type in Redis
  • 3. List Data Type in Redis
  • 4. Set Data type in Redis:
  • 5. Sorted Set in Redis:
  • 6. Streams in Redis:
  • 7. HyperLogLog in Redis:
  • 8. Bitmaps in Redis:
  • 9. Bitfields in Redis
  • 10. Probabilistic in Redis:
  • 11. Geospatial Indexes in Redis:
  • 12. Time-Series in Redis

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Different Data Types in Redis

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1. String Data Type in Redis

Let us now discuss about the various data types in Redis in detail one by one:...

2. Hash Data type in Redis

Redis String is a sequence of bytes which can store sequence of bytes, including text, Object, binary arrays. which can store a maximum of 512 mega bytes in one string. Redis String can also be used like a Redis Key for mapping a string to another string. String Data Types are useful in different types of use cases like: caching HTML fragements or different pages....

3. List Data Type in Redis

Redis Hashes are used to store a list of multiple key- value pairs. it is used to map between a string to another string. It can also used to represent as objects....

4. Set Data type in Redis:

Redis Lists are similar to linked list of String values. Redis Lists can be used to implement stack and queue data structure....

5. Sorted Set in Redis:

Set Data Types in Redis is an un-ordered collection of unique strings. it can be used to detect unique elements in a list, also for intersections, unions, and differences....

6. Streams in Redis:

Sorted Set Data Types in Redis is an ordered-collection of unique strings stored in a sorted form ordered by associated key. when two or more key having same value then, the strings are ordered in lexicographical order. It is similar to Redis Set , the only difference is that Sorted set represents the data in a sorted or ordered way....

7. HyperLogLog in Redis:

A Redis stream is a data structure that acts like an append-only log but also implements several operations to overcome some of the limits of a typical append-only log. These include random access in O(1) time and complex consumption strategies, such as consumer groups....

8. Bitmaps in Redis:

HyperLogLog is a probabilistic data structure that estimates the cardinality of a set. As a probabilistic data structure, HyperLogLog trades perfect accuracy for efficient space utilization....

9. Bitfields in Redis

Bitmaps are not an actual data type, but a set of bit-oriented operations defined on the String type which is treated like a bit vector. Since strings are binary safe blobs and their maximum length is 512 MB, they are suitable to set up to 2^32 different bits....

10. Probabilistic in Redis:

Redis bitfields allow you to set, increase, and get integer values with any number of bits. You can, for instance, work with everything from signed 63-bit numbers to unsigned 1-bit integers....

11. Geospatial Indexes in Redis:

Probabilistic data structures are used to provide approximate answers or estimations for certain operations with reduced memory usage compared to exact data structures. One of the most commonly used probabilistic data structures in Redis is HyperLogLog (HLL). It is used for estimating the cardinality (the number of unique elements) of a set. Redis also offers another probabilistic data structure called Bloom Filters. It checks for presence of an element in a set. Bloom Filters are useful for quickly checking membership in a large dataset without the need for storing the entire dataset in memory. Cuckoo filters are a probabilistic data structure that checks for presence of an element in a set....

12. Time-Series in Redis

Redis Geospatial Indexes helps us to store the coordinates and search for them. this data structure is useful for finding nearby points....

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