Postgres Vector Upsert
Editions
Production use of this feature is available for specific editions only. Contact our sales team for more information.
Postgres Vector Upsert is an orchestration component lets you convert text data stored in your cloud data warehouse into embeddings and then store these embeddings as vectors in your Postgres vector database.
Properties
Name = string
A human-readable name for the component.
Select your cloud data warehouse.
Database = drop-down
The Snowflake database. The special value, [Environment Default], will use the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.
Schema = drop-down
The Snowflake schema. The special value, [Environment Default], will use the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.
Table = string
The Snowflake table that holds your source data.
Catalog = drop-down
Select a Databricks Unity Catalog. The special value, [Environment Default], will use the catalog specified in the Data Productivity Cloud environment setup. Selecting a catalog will determine which databases are available in the next parameter.
Schema (Database) = drop-down
The Databricks schema. The special value, [Environment Default], will use the schema defined in the environment. Read Create and manage schemas to learn more.
Table = drop-down
The Databricks table that holds your source data.
Schema = drop-down
The Redshift schema. The special value, [Environment Default], will use the schema defined in the environment. Read Schemas to learn more.
Table = drop-down
An existing Redshift table to use as the input.
Key Column = drop-down
Set a column as the primary key.
Text Column = drop-down
The column of data to convert into embeddings to then be upserted into your Postgres vector database.
Limit = integer
Set a limit for the numbers of rows from the table to load. The default is 1000.
Embedding Provider = drop-down
The embedding provider is the API service used to convert the search term into a vector. Choose either OpenAI or Amazon Bedrock. The embedding provider receives a search term (e.g. "How do I log in?") and returns a vector.
Choose your provider:
OpenAI API Key = drop-down
Use the drop-down menu to select the corresponding secret definition that denotes the value of your OpenAI API key.
Read Secret definitions to learn how to create a new secret definition.
To create a new OpenAI API key:
- Log in to OpenAI.
- Click your avatar in the top-right of the UI.
- Click View API keys.
- Click + Create new secret key.
- Give a name for your new secret key and click Create secret key.
- Copy your new secret key and save it. Then click Done.
Embedding Model = drop-down
Select an embedding model.
Currently supports:
| Model | Dimension |
|---|---|
| text-embedding-ada-002 | 1536 |
| text-embedding-3-small | 1536 |
| text-embedding-3-large | 3072 |
API Batch Size = integer
Set the size of array of data per API call. The default size is 10. When set to 10, 1000 rows would therefore require 100 API calls.
You may wish to reduce this number if a row contains a high volume of data; and conversely, increase this number for rows with low data volume.
Region = drop-down
Select your AWS region.
Embedding Model = drop-down
Select an embedding model.
Currently supports:
| Model | Dimension |
|---|---|
| Titan Embeddings G1 - Text | 1536 |
Host = string
Your Postgres hostname.
Port = string
The TCP port number the Postgres server listens on. The default is 5432.
Database = string
The name of your Postgres database.
Username = string
Your Postgres username.
Password = drop-down
Use the drop-down menu to select the corresponding secret definition that denotes the value of your Postgres password.
Read Secret definitions to learn how to create a new secret definition.
Schema = drop-down
The Postgres schema. The available schemas are determined by the Postgres database you have provided.
Table = drop-down
The table to load data from. The available tables are determined by the Postgres schema you have selected.
Key Column Name = drop-down
The column in your table to use as the key column.
Text Column Name = drop-down
The column in your table with your original text data.
Embedding Column Name = drop-down
The column in your table used to store your embeddings.
Connection Options = column editor
- Parameter: A JDBC Postgres parameter supported by the database driver.
- Value: A value for the given parameter.
| Snowflake | Databricks | Amazon Redshift |
|---|---|---|
| ✅ | ✅ | ✅ |