Managing Collections

SHOW COLLECTIONS — list collections

Lists all collections in the connected Qdrant instance.

SHOW COLLECTIONS

Output:

✓ 3 collection(s) found
┌──────────────────┐
│ Collection       │
├──────────────────┤
│ articles         │
│ notes            │
│ products         │
└──────────────────┘

SHOW COLLECTION — inspect one collection

Returns collection diagnostics for a single collection using Qdrant's collection info.

Syntax:

SHOW COLLECTION <collection_name>

What it shows:

Point count
Indexed vector count
Segment count
Vector names, dimensions, and distance metrics
Dense vs hybrid topology
Sparse vector modifiers when present
Quantization mode
HNSW configuration
Payload indexes detected by Qdrant
Shard, replica, and write consistency settings

Example:

SHOW COLLECTION research_papers

Output:

OK Collection 'research_papers' diagnostics
Collection: research_papers
  Status               : green
  Points               : 12450
  Indexed vectors      : 12450
  Segments             : 3
  Topology             : hybrid
  Vector 'dense'       : 768 dims, Cosine distance
  Sparse 'sparse'      : modifier=idf
  Quantization         : scalar
  HNSW M               : 16
  HNSW ef_construct    : 100
  Payload indexes:
    category: keyword
    year: integer
  Shards               : 1
  Replicas             : 1
  Write consistency    : 1

Notes:

Topology is dense for standard collections and hybrid when sparse vectors are configured alongside dense vectors.
Dense collections with named vectors still report their vector names and dimensions.
If no payload indexes exist, QQL prints Payload indexes : none.
Raises an error if the collection does not exist.

CREATE COLLECTION — create a collection

Explicitly creates a new empty collection. Collections are also created automatically on the first INSERT, so this command is optional — use it when you want to pre-create a collection before inserting data.

Syntax:

CREATE COLLECTION <collection_name>
CREATE COLLECTION <collection_name> HYBRID
CREATE COLLECTION <collection_name> USING MODEL '<model_name>'
CREATE COLLECTION <collection_name> USING VECTOR '<dense_vector_name>'
CREATE COLLECTION <collection_name> USING HYBRID
CREATE COLLECTION <collection_name> USING HYBRID [DENSE MODEL '<model>'] [DENSE VECTOR '<name>'] [SPARSE VECTOR '<name>']
CREATE COLLECTION <collection_name> WITH VECTORS { on_disk: <bool> }
CREATE COLLECTION <collection_name> WITH HNSW { m, ef_construct, full_scan_threshold, max_indexing_threads, on_disk, payload_m, inline_storage }
CREATE COLLECTION <collection_name> WITH OPTIMIZERS { deleted_threshold, vacuum_min_vector_number, default_segment_number, max_segment_size, memmap_threshold, indexing_threshold, flush_interval_sec, max_optimization_threads, prevent_unoptimized }
CREATE COLLECTION <collection_name> WITH PARAMS { replication_factor, write_consistency_factor, on_disk_payload }
ALTER COLLECTION <collection_name> WITH HNSW { ... }
ALTER COLLECTION <collection_name> WITH VECTORS { ... }
ALTER COLLECTION <collection_name> WITH OPTIMIZERS { ... }
ALTER COLLECTION <collection_name> WITH PARAMS { ... }
ALTER COLLECTION <collection_name> QUANTIZE SCALAR [QUANTILE <0.0–1.0>] [ALWAYS RAM]
ALTER COLLECTION <collection_name> QUANTIZE BINARY [ALWAYS RAM]
ALTER COLLECTION <collection_name> QUANTIZE PRODUCT [ALWAYS RAM]
ALTER COLLECTION <collection_name> QUANTIZE TURBO [BITS <1|1.5|2|4>] [ALWAYS RAM]
ALTER COLLECTION <collection_name> QUANTIZE DISABLED

Any CREATE COLLECTION form can be followed by an optional QUANTIZE clause and one or more WITH ... { ... } config blocks.

Examples:

Dense-only collection (standard, uses default model dimensions):

CREATE COLLECTION research_papers

QQL-created dense collections use the configured dense vector name (dense by default). You can choose a different name explicitly:

CREATE COLLECTION research_papers USING VECTOR 'body'

Dense-only collection pinned to a specific model (768-dimensional):

CREATE COLLECTION research_papers USING MODEL 'BAAI/bge-base-en-v1.5'

Hybrid collection (dense + sparse BM25, default models):

CREATE COLLECTION research_papers HYBRID

Hybrid collection with explicit vector names:

CREATE COLLECTION research_papers USING HYBRID DENSE VECTOR 'emb' SPARSE VECTOR 'lex'

Hybrid collection with a custom dense model:

CREATE COLLECTION research_papers USING HYBRID DENSE MODEL 'BAAI/bge-base-en-v1.5'

Dense collection with payload-aware HNSW links:

CREATE COLLECTION research_papers WITH HNSW { payload_m: 16 }

When USING MODEL is omitted, the collection uses the default embedding model's dimensions (384 for all-MiniLM-L6-v2). If the collection already exists, the command succeeds with a message and does nothing.

Collection config blocks

QQL supports the same config blocks on both CREATE COLLECTION and ALTER COLLECTION:

WITH VECTORS { on_disk }
WITH HNSW { m, ef_construct, full_scan_threshold, max_indexing_threads, on_disk, payload_m, inline_storage }
WITH OPTIMIZERS { deleted_threshold, vacuum_min_vector_number, default_segment_number, max_segment_size, memmap_threshold, indexing_threshold, flush_interval_sec, max_optimization_threads, prevent_unoptimized }
WITH PARAMS { replication_factor, write_consistency_factor, on_disk_payload } on create
WITH PARAMS { replication_factor, write_consistency_factor, read_fan_out_factor, read_fan_out_delay_ms, on_disk_payload } on alter
ALTER COLLECTION ... QUANTIZE ... supports the same quantization forms as create, plus QUANTIZE DISABLED

ALTER COLLECTION ... WITH VECTORS { ... } can update unnamed collections or named collections with one dense vector. Collections with multiple dense vectors are rejected because this syntax has no vector-name target.

Example:

CREATE COLLECTION tenant_docs USING HYBRID WITH HNSW { payload_m: 16, m: 32 }
ALTER COLLECTION tenant_docs WITH OPTIMIZERS { indexing_threshold: 10000 }

Quantization — QUANTIZE clause

Quantization reduces the memory footprint of vector collections and speeds up search at the cost of a small, controllable accuracy loss. QQL supports all four Qdrant quantization strategies via an optional QUANTIZE clause appended to CREATE COLLECTION.

Four strategies:

Type	Compression	Accuracy	Best For
`SCALAR`	4× (float32 → int8)	< 1% loss	Most collections — best balance
`TURBO`	8–32× (4-bit to 1-bit)	Low–medium	Better recall than BINARY at same storage budget
`BINARY`	32× (float32 → 1-bit)	Higher loss	Speed priority; centered distributions only
`PRODUCT`	4× (configurable)	Variable	Memory-constrained deployments

Full syntax:

CREATE COLLECTION <name> ... QUANTIZE SCALAR [QUANTILE <0.0–1.0>] [ALWAYS RAM]
CREATE COLLECTION <name> ... QUANTIZE TURBO  [BITS <1|1.5|2|4>]   [ALWAYS RAM]
CREATE COLLECTION <name> ... QUANTIZE BINARY  [ALWAYS RAM]
CREATE COLLECTION <name> ... QUANTIZE PRODUCT [ALWAYS RAM]

QUANTILE <float> — (SCALAR only) calibration quantile for the INT8 conversion; defaults to Qdrant's built-in default (0.99) when omitted.
BITS <depth> — (TURBO only) bit depth passed to the Qdrant SDK:
- 4 — 4-bit (default when BITS is omitted; server applies its own default)
- 2 — 2-bit
- 1.5 — 1.5-bit
- 1 — 1-bit
Compression ratios (8×, 16×, 24×, 32×) and recall characteristics are Qdrant server-side behaviors. QQL maps the BITS value to the SDK model and passes it to Qdrant; actual results depend on your Qdrant server version.
ALWAYS RAM — keep the quantized vectors in RAM at all times, regardless of the collection's on_disk setting. Improves search throughput at the cost of higher RAM usage for the compressed index. The original full-precision vectors are stored and managed independently of this flag. Supported by all four quantization types.
QUANTIZE always appears after all other clauses (HYBRID, USING MODEL, etc.).
For PRODUCT, the compression ratio is fixed at 4× in this version.
For TURBO, Cosine, Dot, and Euclidean distance are supported by the Qdrant server when TurboQuant is enabled.
When used with HYBRID collections, quantization applies only to the dense vector.

Examples:

Scalar quantization (recommended default):

CREATE COLLECTION research_papers QUANTIZE SCALAR

Scalar with explicit calibration and quantized vectors pinned to RAM:

CREATE COLLECTION research_papers QUANTIZE SCALAR QUANTILE 0.95 ALWAYS RAM

TurboQuant — default 4-bit (8× compression, good recall):

CREATE COLLECTION research_papers QUANTIZE TURBO

TurboQuant — 2-bit (16× compression):

CREATE COLLECTION research_papers QUANTIZE TURBO BITS 2

TurboQuant — 1.5-bit (24× compression) with quantized vectors pinned to RAM:

CREATE COLLECTION research_papers QUANTIZE TURBO BITS 1.5 ALWAYS RAM

TurboQuant — 1-bit (32× compression, same ratio as BINARY but better recall):

CREATE COLLECTION research_papers QUANTIZE TURBO BITS 1

Binary quantization for large high-dimensional embeddings:

CREATE COLLECTION research_papers QUANTIZE BINARY

Product quantization for maximum memory savings:

CREATE COLLECTION research_papers QUANTIZE PRODUCT ALWAYS RAM

Combined with hybrid collection:

CREATE COLLECTION research_papers HYBRID QUANTIZE SCALAR
CREATE COLLECTION research_papers HYBRID QUANTIZE TURBO BITS 2

Combined with a pinned model:

CREATE COLLECTION research_papers USING MODEL 'BAAI/bge-base-en-v1.5' QUANTIZE SCALAR QUANTILE 0.99
CREATE COLLECTION research_papers USING MODEL 'BAAI/bge-base-en-v1.5' QUANTIZE TURBO BITS 2

Combined with hybrid + dense model:

CREATE COLLECTION research_papers USING HYBRID DENSE MODEL 'BAAI/bge-base-en-v1.5' QUANTIZE TURBO

Valid combinations:

Base form	+ SCALAR	+ TURBO	+ BINARY	+ PRODUCT
`CREATE COLLECTION name`	✓	✓	✓	✓
`... HYBRID`	✓	✓	✓	✓
`... USING MODEL 'x'`	✓	✓	✓	✓
`... USING HYBRID`	✓	✓	✓	✓
`... USING HYBRID DENSE MODEL 'x'`	✓	✓	✓	✓

INSERT and SEARCH on quantized collections work exactly the same as on non-quantized ones — no changes to INSERT or SEARCH syntax are needed.

CREATE INDEX — create a payload index

Creates a payload index on a collection field. Payload indexes speed up WHERE clause filtering by allowing Qdrant to efficiently match on indexed fields.

Syntax:

CREATE INDEX ON COLLECTION <collection_name> FOR <field_name> TYPE <schema_type>
CREATE INDEX ON COLLECTION <collection_name> FOR <field_name> TYPE <schema_type> WITH { ... }

Supported schema types:

Type	Description
`keyword`	Exact string match (e.g. status, category)
`integer`	Whole numbers
`float`	Decimal numbers
`bool`	Boolean values
`text`	Full-text search (enables `MATCH` operators)
`geo`	Geospatial coordinates
`datetime`	Date/time values
`uuid`	UUID payload values

Examples:

CREATE INDEX ON COLLECTION articles FOR category TYPE keyword
CREATE INDEX ON COLLECTION articles FOR tenant_id TYPE keyword WITH {is_tenant: true, on_disk: true, enable_hnsw: true}
CREATE INDEX ON COLLECTION articles FOR year TYPE integer
CREATE INDEX ON COLLECTION articles FOR doc_id TYPE uuid
CREATE INDEX ON COLLECTION articles FOR title TYPE text
CREATE INDEX ON COLLECTION articles FOR title TYPE text WITH {tokenizer: 'word', min_token_len: 2, max_token_len: 20, lowercase: true, phrase_matching: true}
CREATE INDEX ON COLLECTION articles FOR meta.author TYPE keyword

Advanced options currently supported:

keyword / uuid
- is_tenant: true|false
- on_disk: true|false
- enable_hnsw: true|false
text
- tokenizer: 'prefix'|'whitespace'|'word'|'multilingual'
- min_token_len: <int>
- max_token_len: <int>
- lowercase: true|false
- ascii_folding: true|false
- phrase_matching: true|false
- stopwords: 'english' or stopwords: ['a', 'the']
- on_disk: true|false
- enable_hnsw: true|false

Rules:

The collection must already exist. Raises an error otherwise.
Indexes are idempotent — creating the same index twice succeeds silently.
Advanced WITH { ... } options are currently supported only for keyword, uuid, and text.

DROP COLLECTION — delete a collection

Permanently deletes a collection and all points inside it. This operation is irreversible.

DROP COLLECTION old_experiments

Raises an error if the collection does not exist.

DELETE — remove points

Deletes one or more points from a collection by specific ID or by a WHERE filter.

Syntax:

DELETE FROM <collection_name> WHERE id = '<point_id>'
DELETE FROM <collection_name> WHERE id = <integer_id>
DELETE FROM <collection_name> WHERE <filter>

Examples:

-- Delete by UUID
DELETE FROM articles WHERE id = '3f2e1a4b-8c91-4d0e-b123-abc123def456'

-- Delete by integer ID
DELETE FROM articles WHERE id = 42

-- Delete all points matching a filter
DELETE FROM articles WHERE category = 'archived'

-- Delete with a compound filter
DELETE FROM articles WHERE year < 2020 AND status = 'draft'

Notes:

If no points match the filter or ID, the operation succeeds silently with a count of 0.
The collection itself must exist; deleting from a non-existent collection raises an error.

UPDATE SET VECTOR — replace a point's dense vector

Replaces the stored dense vector for a single point identified by its ID. The point must already exist in the collection. Use this when you want to refresh an embedding without changing the payload.

Syntax:

UPDATE <collection> SET VECTOR WHERE id = '<point_id>' [<vector>]
UPDATE <collection> SET VECTOR WHERE id = <integer_id>  [<vector>]
UPDATE <collection> SET VECTOR '<dense_vector_name>' WHERE id = '<point_id>' [<vector>]

The vector is provided as a JSON-style float array [v1, v2, ..., vN]. The array length must match the collection's configured vector dimensions.

Examples:

-- Replace vector by UUID
UPDATE articles SET VECTOR WHERE id = '3f2e1a4b-8c91-4d0e-b123-abc123def456' [0.1, 0.2, 0.3, 0.4]

-- Replace vector by integer ID
UPDATE articles SET VECTOR WHERE id = 42 [0.1, 0.2, 0.3, 0.4]

-- Replace a specific named vector
UPDATE articles SET VECTOR 'body' WHERE id = '3f2e1a4b-8c91-4d0e-b123-abc123def456' [0.1, 0.2, 0.3, 0.4]

Notes:

Only single-point updates are supported (by ID). Bulk or filter-based vector updates are not supported.
The point must already exist; this operation does not create new points.
The collection must exist; updating from a non-existent collection raises an error.
For named-vector collections, QQL updates the only dense vector when the target is unambiguous. Use SET VECTOR '<name>' when a collection has multiple dense vectors.
Sparse vectors are managed separately.

UPDATE SET PAYLOAD — merge fields into a point's payload

Merges new key/value pairs into the payload of one or more points. Existing fields not mentioned in the update are preserved (additive merge, not a full replace). Use a WHERE filter to update multiple points at once.

Syntax:

UPDATE <collection> SET PAYLOAD WHERE id = '<point_id>' {<payload>}
UPDATE <collection> SET PAYLOAD WHERE id = <integer_id>  {<payload>}
UPDATE <collection> SET PAYLOAD WHERE <filter>            {<payload>}

Examples:

-- Update a single point by UUID
UPDATE articles SET PAYLOAD WHERE id = '3f2e1a4b-8c91-4d0e-b123-abc123def456' {'year': 2025, 'status': 'active'}

-- Update a single point by integer ID
UPDATE articles SET PAYLOAD WHERE id = 42 {'category': 'tech'}

-- Update all points matching a filter
UPDATE articles SET PAYLOAD WHERE category = 'draft' {'status': 'published'}

-- Compound filter update
UPDATE articles SET PAYLOAD WHERE year < 2020 AND status = 'draft' {'archived': true}

Notes:

Merge semantics: only the fields in {…} are written; all other existing payload fields are preserved.
If no points match the filter, the operation succeeds silently with no changes.
The collection must exist; updating from a non-existent collection raises an error.
All WHERE filter operators supported by DELETE are also supported here (see WHERE Filters).

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Managing Collections

SHOW COLLECTIONS — list collections

SHOW COLLECTION — inspect one collection

CREATE COLLECTION — create a collection

Collection config blocks

Quantization — QUANTIZE clause

CREATE INDEX — create a payload index

DROP COLLECTION — delete a collection

DELETE — remove points

UPDATE SET VECTOR — replace a point's dense vector

UPDATE SET PAYLOAD — merge fields into a point's payload

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Managing Collections

SHOW COLLECTIONS — list collections

SHOW COLLECTION — inspect one collection

CREATE COLLECTION — create a collection

Collection config blocks

Quantization — QUANTIZE clause

CREATE INDEX — create a payload index

DROP COLLECTION — delete a collection

DELETE — remove points

UPDATE SET VECTOR — replace a point's dense vector

UPDATE SET PAYLOAD — merge fields into a point's payload