Search Shortcut cmd + k | ctrl + k
Search
cmd+k
ctrl+k
- Installation
- Guides
- Overview
- Data Import & Export
- Overview
- CSV Import
- CSV Export
- Parquet Import
- Parquet Export
- Querying Parquet Files
- HTTP Parquet Import
- S3 Parquet Import
- S3 Parquet Export
- S3 Iceberg Import
- S3 Express One
- GCS Import
- Cloudflare R2 Import
- JSON Import
- JSON Export
- Excel Import
- Excel Export
- MySQL Import
- PostgreSQL Import
- SQLite Import
- Directly Reading Files
- Performance
- Overview
- Schema
- Indexing
- Environment
- File Formats
- How to Tune Workloads
- My Workload Is Slow
- Benchmarks
- Meta Queries
- Describe Table
- EXPLAIN: Inspect Query Plans
- EXPLAIN ANALYZE: Profile Queries
- List Tables
- Summarize
- DuckDB Environment
- ODBC
- Python
- Installation
- Executing SQL
- Jupyter Notebooks
- SQL on Pandas
- Import from Pandas
- Export to Pandas
- SQL on Arrow
- Import from Arrow
- Export to Arrow
- Relational API on Pandas
- Multiple Python Threads
- Integration with Ibis
- Integration with Polars
- Using fsspec Filesystems
- SQL Features
- SQL Editors
- Data Viewers
- Documentation
- Overview
- Connect
- Data Import
- Overview
- CSV Files
- JSON Files
- Multiple Files
- Parquet Files
- Partitioning
- Appender
- INSERT Statements
- Client APIs
- Overview
- C
- Overview
- Startup
- Configuration
- Query
- Data Chunks
- Values
- Types
- Prepared Statements
- Appender
- Table Functions
- Replacement Scans
- API Reference
- C++
- CLI
- Go
- Java
- Julia
- Node.js
- Python
- Overview
- Data Ingestion
- Conversion between DuckDB and Python
- DB API
- Relational API
- Function API
- Types API
- Expression API
- Spark API
- API Reference
- Known Python Issues
- R
- Rust
- Swift
- Wasm
- ADBC
- ODBC
- Configuration
- SQL
- Introduction
- Statements
- Overview
- ALTER TABLE
- ALTER VIEW
- ATTACH/DETACH
- CALL
- CHECKPOINT
- COMMENT ON
- COPY
- CREATE INDEX
- CREATE MACRO
- CREATE SCHEMA
- CREATE SECRET
- CREATE SEQUENCE
- CREATE TABLE
- CREATE VIEW
- CREATE TYPE
- DELETE
- DROP
- EXPORT/IMPORT DATABASE
- INSERT
- PIVOT
- Profiling
- SELECT
- SET/RESET
- Transaction Management
- UNPIVOT
- UPDATE
- USE
- VACUUM
- Query Syntax
- SELECT
- FROM & JOIN
- WHERE
- GROUP BY
- GROUPING SETS
- HAVING
- ORDER BY
- LIMIT
- SAMPLE
- Unnesting
- WITH
- WINDOW
- QUALIFY
- VALUES
- FILTER
- Set Operations
- Prepared Statements
- Data Types
- Overview
- Array
- Bitstring
- Blob
- Boolean
- Date
- Enum
- Interval
- List
- Literal Types
- Map
- NULL Values
- Numeric
- Struct
- Text
- Time
- Timestamp
- Time Zones
- Union
- Typecasting
- Expressions
- Overview
- CASE Statement
- Casting
- Collations
- Comparisons
- IN Operator
- Logical Operators
- Star Expression
- Subqueries
- Functions
- Overview
- Bitstring Functions
- Blob Functions
- Date Format Functions
- Date Functions
- Date Part Functions
- Enum Functions
- Interval Functions
- Lambda Functions
- Nested Functions
- Numeric Functions
- Pattern Matching
- Regular Expressions
- Text Functions
- Time Functions
- Timestamp Functions
- Timestamp with Time Zone Functions
- Utility Functions
- Aggregate Functions
- Constraints
- Indexes
- Information Schema
- Metadata Functions
- Keywords and Identifiers
- Samples
- Window Functions
- Extensions
- Development
- DuckDB Repositories
- Testing
- Overview
- Writing Tests
- sqllogictest
- Debugging
- Result Verification
- Persistent Testing
- Loops
- Multiple Connections
- Catch
- Internals Overview
- Storage Versions & Format
- Execution Format
- Profiling
- Release Calendar
- Building
- Benchmark Suite
- Sitemap
- Why DuckDB
- Media
- FAQ
- Code of Conduct
- Live Demo
Name | Aliases | Description |
---|---|---|
BLOB |
BYTEA , BINARY , VARBINARY |
variable-length binary data |
The blob (Binary Large OBject) type represents an arbitrary binary object stored in the database system. The blob type can contain any type of binary data with no restrictions. What the actual bytes represent is opaque to the database system.
-- create a blob value with a single byte (170)
SELECT '\xAA'::BLOB;
-- create a blob value with three bytes (170, 171, 172)
SELECT '\xAA\xAB\xAC'::BLOB;
-- create a blob value with two bytes (65, 66)
SELECT 'AB'::BLOB;
Blobs are typically used to store non-textual objects that the database does not provide explicit support for, such as images. While blobs can hold objects up to 4GB in size, typically it is not recommended to store very large objects within the database system. In many situations it is better to store the large file on the file system, and store the path to the file in the database system in a VARCHAR
field.
Functions
See Blob Functions.
About this page
Last modified: 2024-03-18