Redis
In-memory data store used as a database, cache and message broker, read over the Redis protocol with client libraries.
- Category
- Cloud & Data Platforms
- Type
- Database
- Interface
- database interface
- Built with
- Connect Anything
- Credentials
- Username and password, Vendor credentials
- Docs
- Redis API docs
02Data
What you can sync.
- Keys
- Hashes
- Streams
- Sorted sets
- Json documents
Load Redis keys into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other Redis data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- A username and password
- Other credentials
Redis uses a username and password or other credentials. You add the credentials once, when the AI asks for them, and it tells you where to create them in Redis if you need help.
04How it works
How it works in DataMind.
-
Pick Redis.
Open Lake, pick Redis in the source picker and name the connection. Connect Anything opens with a ready prompt that points the AI at the Redis API docs.
-
Answer a few questions.
The AI reads the Redis documentation, then asks which credentials you will use, which data to sync (for example keys and hashes), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
The connector agent writes a Python connector for Redis, tests it against the live API and shows you sample rows. Then the data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
