Built-in Redis Modules

Redis includes several built-in modules that extend its functionality with specialized data types and processing capabilities. These modules require compiling Redis with the BUILD_WITH_MODULES=yes flag.

Compilation RequirementBuilt-in modules are only available when Redis is compiled with:

make BUILD_WITH_MODULES=yes

See the Build from Source guide for platform-specific instructions.

Available Built-in Modules

When compiled with BUILD_WITH_MODULES=yes, Redis includes:

RedisJSON - Native JSON document storage with JSONPath queries
RediSearch - Full-text search, secondary indexing, and query engine
RedisTimeSeries - Time-series data storage with downsampling and aggregation
RedisBloom - Probabilistic data structures (Bloom filters, Cuckoo filters, Count-Min sketch, Top-K)

Module Structure

The built-in modules are located in the modules/ directory:

modules/
├── redisjson/      # JSON module
├── redisearch/     # Search and query engine
├── redistimeseries/# Time-series module
├── redisbloom/     # Probabilistic data structures
└── vector-sets/    # Vector similarity search

RedisJSON

Stores, updates, and queries JSON documents as native Redis data types.

Features

JSONPath syntax for querying and manipulation
Atomic operations on JSON documents
Integration with RediSearch for indexing
Efficient memory representation

Example Commands

# Store a JSON document
JSON.SET user:1 $ '{"name":"Alice","age":30,"email":"[email protected]"}'

# Get the entire document
JSON.GET user:1
# Returns: {"name":"Alice","age":30,"email":"[email protected]"}

# Get a specific field
JSON.GET user:1 $.name
# Returns: ["Alice"]

# Update a field
JSON.SET user:1 $.age 31

# Increment a numeric field
JSON.NUMINCRBY user:1 $.age 1

# Append to an array
JSON.ARRAPPEND user:1 $.tags '"premium"'

# Delete a field
JSON.DEL user:1 $.email

Key Commands

JSON.SET - Set JSON document or value
JSON.GET - Get JSON document or value
JSON.DEL - Delete JSON document or value
JSON.NUMINCRBY - Increment number value
JSON.ARRAPPEND - Append to array
JSON.ARRPOP - Pop from array
JSON.OBJKEYS - Get object keys
JSON.TYPE - Get type of value

RediSearch

Provides full-text search, secondary indexes, and a query engine for Redis data.

Features

Full-text search with stemming and fuzzy matching
Secondary indexes on hash and JSON documents
Vector similarity search
Geospatial queries
Aggregations and grouping
Phonetic matching

Example: Creating an Index

# Create index on hash documents
FT.CREATE idx:users ON HASH PREFIX 1 user: SCHEMA
  name TEXT SORTABLE
  email TAG
  age NUMERIC SORTABLE
  location GEO

# Add documents (as hashes)
HSET user:1 name "Alice Smith" email "[email protected]" age 30
HSET user:2 name "Bob Jones" email "[email protected]" age 25

# Search for users
FT.SEARCH idx:users "Alice"

# Search with filters
FT.SEARCH idx:users "*" FILTER age 25 35

# Search and sort
FT.SEARCH idx:users "*" SORTBY age ASC

Example: JSON Index

# Create index on JSON documents
FT.CREATE idx:products ON JSON PREFIX 1 product: SCHEMA
  $.name AS name TEXT
  $.price AS price NUMERIC
  $.category AS category TAG
  $.location AS location GEO

# Add JSON documents
JSON.SET product:1 $ '{"name":"Laptop","price":999.99,"category":"electronics"}'
JSON.SET product:2 $ '{"name":"Desk","price":299.99,"category":"furniture"}'

# Search
FT.SEARCH idx:products "laptop"

# Aggregations
FT.AGGREGATE idx:products "*"
  GROUPBY 1 @category
  REDUCE AVG 1 @price AS avg_price

Key Commands

FT.CREATE - Create index
FT.SEARCH - Search index
FT.AGGREGATE - Run aggregation query
FT.SUGADD - Add suggestion
FT.SUGGET - Get suggestions
FT.INFO - Get index info
FT.DROPINDEX - Drop index

RedisTimeSeries

Stores and queries time-series data with automatic downsampling and aggregations.

Features

High-performance time-series data storage
Automatic downsampling with configurable aggregations
Retention policies
Compaction rules
Range queries with aggregations
Labels for filtering and grouping

Example Commands

# Create time series
TS.CREATE temperature:sensor1
  RETENTION 86400000
  LABELS sensor_id 1 location warehouse

# Add samples
TS.ADD temperature:sensor1 * 22.5
TS.ADD temperature:sensor1 * 23.1
TS.ADD temperature:sensor1 * 22.8

# Add multiple samples
TS.MADD temperature:sensor1 1609459200000 21.5
        temperature:sensor1 1609459260000 22.0
        temperature:sensor1 1609459320000 22.3

# Query range
TS.RANGE temperature:sensor1 1609459200000 1609462800000

# Query with aggregation
TS.RANGE temperature:sensor1 1609459200000 1609462800000
  AGGREGATION avg 3600000  # 1-hour buckets

# Create downsampling rule
TS.CREATE temperature:sensor1:hourly
TS.CREATERULE temperature:sensor1 temperature:sensor1:hourly
  AGGREGATION avg 3600000

# Query by labels
TS.MGET FILTER location=warehouse

# Multi-range query
TS.MRANGE 1609459200000 1609462800000
  AGGREGATION avg 3600000
  FILTER location=warehouse

Key Commands

TS.CREATE - Create time series
TS.ADD - Add sample
TS.MADD - Add multiple samples
TS.RANGE - Query range
TS.MRANGE - Multi-series range query
TS.GET - Get latest sample
TS.MGET - Get latest from multiple series
TS.CREATERULE - Create compaction rule
TS.INFO - Get series info

RedisBloom

Probabilistic data structures for approximate membership and counting.

Bloom Filter

Tests whether an element is a member of a set with tunable false positive rate.

# Create Bloom filter
BF.RESERVE emails 0.001 10000
# Error rate: 0.1%, capacity: 10,000 items

# Add items
BF.ADD emails "[email protected]"
BF.MADD emails "[email protected]" "[email protected]"

# Check membership
BF.EXISTS emails "[email protected]"
# Returns: 1 (probably exists)

BF.EXISTS emails "[email protected]"
# Returns: 0 (definitely does not exist)

# Check multiple
BF.MEXISTS emails "[email protected]" "[email protected]"
# Returns: [1, 0]

Cuckoo Filter

Similar to Bloom filter but supports deletion.

# Create Cuckoo filter
CF.RESERVE usernames 10000

# Add items
CF.ADD usernames "alice"
CF.ADDNX usernames "bob"  # Add only if not exists

# Check membership
CF.EXISTS usernames "alice"

# Delete item
CF.DEL usernames "alice"

# Count occurrences (approximate)
CF.COUNT usernames "bob"

Count-Min Sketch

Estimates frequency of items in a stream.

# Create Count-Min Sketch
CMS.INITBYDIM page_views 1000 5
# Width: 1000, depth: 5

# Increment counters
CMS.INCRBY page_views /home 1
CMS.INCRBY page_views /products 1
CMS.INCRBY page_views /home 1

# Query count
CMS.QUERY page_views /home
# Returns: 2 (approximate)

# Query multiple
CMS.QUERY page_views /home /products /about
# Returns: [2, 1, 0]

Top-K

Tracks top K most frequent items.

# Create Top-K
TOPK.RESERVE trending 10 1000 5 0.9
# k=10, width=1000, depth=5, decay=0.9

# Add items
TOPK.ADD trending "apple" "banana" "apple" "cherry" "apple"

# Query if item is in top-k
TOPK.QUERY trending "apple"
# Returns: 1 (yes)

# List top-k items
TOPK.LIST trending
# Returns: ["apple", "banana", "cherry", ...]

# List with counts
TOPK.LIST trending WITHCOUNT
# Returns: ["apple", 3, "banana", 1, "cherry", 1, ...]

Key Commands

Bloom Filter:

BF.RESERVE - Create filter
BF.ADD - Add item
BF.MADD - Add multiple items
BF.EXISTS - Check membership
BF.MEXISTS - Check multiple

Cuckoo Filter:

CF.RESERVE - Create filter
CF.ADD - Add item
CF.EXISTS - Check membership
CF.DEL - Delete item
CF.COUNT - Count occurrences

Count-Min Sketch:

CMS.INITBYDIM - Create sketch
CMS.INCRBY - Increment counter
CMS.QUERY - Query count
CMS.MERGE - Merge sketches

Top-K:

TOPK.RESERVE - Create Top-K
TOPK.ADD - Add items
TOPK.QUERY - Query membership
TOPK.LIST - List top items
TOPK.COUNT - Count item

Module Configuration

When running Redis with built-in modules, use the redis-full.conf configuration:

redis-server redis-full.conf

This configuration automatically loads all built-in modules.

Manual Loading

You can also load modules individually:

redis-server --loadmodule /path/to/redisjson.so
             --loadmodule /path/to/redisearch.so
             --loadmodule /path/to/redistimeseries.so
             --loadmodule /path/to/redisbloom.so

Checking Loaded Modules

redis-cli MODULE LIST

Output:

1) 1) "name"
   2) "ReJSON"
   3) "ver"
   4) (integer) 20000
2) 1) "name"
   2) "search"
   3) "ver"
   4) (integer) 20400
3) 1) "name"
   2) "timeseries"
   3) "ver"
   4) (integer) 11000
4) 1) "name"
   2) "bf"
   3) "ver"
   4) (integer) 20205

Use Cases

E-commerce Application

# Store product catalog as JSON
JSON.SET product:1 $ '{"name":"Laptop","price":999,"category":"electronics","tags":["portable","work"]}'

# Create search index
FT.CREATE idx:products ON JSON PREFIX 1 product: SCHEMA
  $.name AS name TEXT
  $.price AS price NUMERIC
  $.category AS category TAG

# Track page views with Count-Min Sketch
CMS.INCRBY views product:1 1

# Track trending products with Top-K
TOPK.ADD trending product:1

# Deduplicate viewed products with Bloom filter
BF.ADD user:123:viewed product:1

IoT Monitoring

# Create time series for sensor data
TS.CREATE sensor:temp:1
  RETENTION 604800000  # 7 days
  LABELS sensor_id 1 type temperature room kitchen

# Add readings
TS.ADD sensor:temp:1 * 22.5

# Create hourly aggregation
TS.CREATE sensor:temp:1:hourly
TS.CREATERULE sensor:temp:1 sensor:temp:1:hourly AGGREGATION avg 3600000

# Query recent data
TS.RANGE sensor:temp:1 - + LATEST

# Query all sensors in kitchen
TS.MGET FILTER room=kitchen

# Store user profiles as JSON
JSON.SET user:1 $ '{"username":"alice","followers":1500,"posts":[]}}'

# Track unique visitors with HyperLogLog (Redis core)
PFADD visitors:today user:1 user:2 user:3
PFCOUNT visitors:today

# Track trending hashtags with Top-K
TOPK.ADD trending:hashtags "#redis" "#database" "#redis"

# Deduplicate content with Bloom filter
BF.ADD seen:posts "post:12345"

Performance Considerations

Memory UsageBuilt-in modules increase memory usage. Monitor with:

redis-cli INFO memory
redis-cli MEMORY USAGE key

Best Practices

Use appropriate retention policies for time-series data
Size Bloom filters correctly - balance false positive rate vs memory
Create indexes selectively - only index fields you query
Use downsampling for long-term time-series storage
Monitor module memory with INFO commands

Documentation

For detailed documentation on each module:

Next Steps

Module API Overview

Learn about the modules API

Create Custom Modules

Build your own Redis module

Commands

Modules API

Protocol

Built-in Redis Modules

Available Built-in Modules

Module Structure

RedisJSON

Features

Example Commands

Key Commands

RediSearch

Features

Example: Creating an Index

Example: JSON Index

Key Commands

RedisTimeSeries

Features

Example Commands

Key Commands

RedisBloom

Bloom Filter

Cuckoo Filter

Count-Min Sketch

Top-K

Key Commands

Module Configuration

Manual Loading

Checking Loaded Modules

Use Cases

E-commerce Application

IoT Monitoring

Performance Considerations

Best Practices

Documentation

Next Steps

Module API Overview

Create Custom Modules

Build docs developers (and LLMs) love

Commands

Modules API

Protocol

​Available Built-in Modules

​Module Structure

​RedisJSON

​Features

​Example Commands

​Key Commands

​RediSearch

​Features

​Example: Creating an Index

​Example: JSON Index

​Key Commands

​RedisTimeSeries

​Features

​Example Commands

​Key Commands

​RedisBloom

​Bloom Filter

​Cuckoo Filter

​Count-Min Sketch

​Top-K

​Key Commands

​Module Configuration

​Manual Loading

​Checking Loaded Modules

​Use Cases

​E-commerce Application

​IoT Monitoring

​Social Media Analytics

​Performance Considerations

​Best Practices

​Documentation

​Next Steps

Module API Overview

Create Custom Modules

Build docs developers (and LLMs) love

Available Built-in Modules

Module Structure

RedisJSON

Features

Example Commands

Key Commands

RediSearch

Features

Example: Creating an Index

Example: JSON Index

Key Commands

RedisTimeSeries

Features

Example Commands

Key Commands

RedisBloom

Bloom Filter

Cuckoo Filter

Count-Min Sketch

Top-K

Key Commands

Module Configuration

Manual Loading

Checking Loaded Modules

Use Cases

E-commerce Application

IoT Monitoring

Social Media Analytics

Performance Considerations

Best Practices

Documentation

Next Steps