/redis-search

Choose the Correct Field Type

Each field type has different capabilities and performance characteristics. Use the narrowest type that supports your access pattern — TAG is roughly 10× faster than TEXT for exact-match filtering, and NUMERIC SORTABLE is the only fast path for range sorts.

Correct: Use TAG for exact matching (Bicycle dataset).

FT.CREATE idx:bicycle ON HASH PREFIX 1 bicycle:
    SCHEMA
        model        TEXT WEIGHT 2.0
        description  TEXT
        brand        TAG
        condition    TAG
        price        NUMERIC SORTABLE

# Query: exact-match TAG filter on brand
FT.SEARCH idx:bicycle "@brand:{Velorim} @condition:{new}" DIALECT 2

Incorrect: Using TEXT when you don't need full-text features.

# Overkill: TEXT for brand/condition adds unnecessary tokenization
FT.CREATE idx:bicycle ON HASH PREFIX 1 bicycle:
    SCHEMA
        model       TEXT
        brand       TEXT
        condition   TEXT

Correct: Use GEO for points, GEOSHAPE for areas.

# GEO for point locations (stores, users)
FT.CREATE idx:bicycle ON HASH PREFIX 1 bicycle:
    SCHEMA
        store_location GEO

# GEOSHAPE for areas (delivery zones, boundaries)
FT.CREATE idx:zones ON JSON PREFIX 1 zone:
    SCHEMA
        $.boundary AS boundary GEOSHAPE

For JSON-path fields ($.path AS alias), see json-indexing.md. For vector fields, see algorithm-choice.md.

Client mirrors

# redis-py — STEP_START field_types
# Mirrors doctests/search_quickstart.py
from redis import Redis
from redis.commands.search.field import TextField, TagField, NumericField, GeoField
from redis.commands.search.indexDefinition import IndexDefinition, IndexType

r = Redis()
schema = (
    TextField("model", weight=2.0),
    TextField("description"),
    TagField("brand"),
    TagField("condition"),
    NumericField("price", sortable=True),
    GeoField("store_location"),
)
r.ft("idx:bicycle").create_index(
    schema,
    definition=IndexDefinition(prefix=["bicycle:"], index_type=IndexType.HASH))
# STEP_END

// Jedis — STEP_START field_types
// Mirrors SearchQuickstartExample.java
import redis.clients.jedis.UnifiedJedis;
import redis.clients.jedis.search.FTCreateParams;
import redis.clients.jedis.search.IndexDataType;
import redis.clients.jedis.search.schemafields.*;

try (UnifiedJedis jedis = new UnifiedJedis("redis://localhost:6379")) {
    jedis.ftCreate("idx:bicycle",
        FTCreateParams.createParams().on(IndexDataType.HASH).prefix("bicycle:"),
        TextField.of("model").weight(2.0),
        TextField.of("description"),
        TagField.of("brand"),
        TagField.of("condition"),
        NumericField.of("price").sortable(),
        GeoField.of("store_location"));
}
// STEP_END

Upstream sources

• redis-py: doctests/search_quickstart.py
• Jedis: SearchQuickstartExample.java
• Reference: Redis Search Field Types