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🔌 ConnectorsSnowflake Redis Sinks

Last Updated: 3/19/2026

Snowflake and Redis Sinks

Feldera supports writing pipeline output to Snowflake data warehouses and Redis key-value stores. These connectors enable integration with downstream analytics and caching systems.

Redis Output Connector

The Redis output connector writes pipeline output to Redis as key-value pairs or streams.

Basic Configuration

outputs:
  cache:
    stream: user_stats
    connector_config:
      transport:
        name: redis_output
        config:
          connection_string: "redis://localhost:6379"
      format:
        name: json

Configuration Options

Connection:

  • connection_string — Redis connection URL (e.g., "redis://localhost:6379", "rediss://user:pass@host:6380")

Authentication:

  • Include credentials in the connection string: "redis://username:password@host:port"
  • Use TLS with rediss:// scheme

Key-Value Mode

Write output as key-value pairs using an index:

CREATE TABLE user_stats (
    user_id INTEGER PRIMARY KEY,
    event_count INTEGER,
    last_event TIMESTAMP
);
 
CREATE INDEX idx_user_stats ON user_stats(user_id);
outputs:
  cache:
    stream: user_stats
    index: idx_user_stats
    connector_config:
      transport:
        name: redis_output
        config:
          connection_string: "redis://localhost:6379"
      format:
        name: json

The connector uses the index key as the Redis key and the full record as the value.

Stream Mode

Write output as a Redis stream (without an index):

outputs:
  events:
    stream: processed_events
    connector_config:
      transport:
        name: redis_output
        config:
          connection_string: "redis://localhost:6379"
      format:
        name: json

Use Cases

Caching query results:

CREATE MATERIALIZED VIEW top_users AS
SELECT user_id, COUNT(*) as count
FROM events
GROUP BY user_id
ORDER BY count DESC
LIMIT 100;

Real-time leaderboards:

CREATE MATERIALIZED VIEW leaderboard AS
SELECT 
    user_id,
    score,
    RANK() OVER (ORDER BY score DESC) as rank
FROM user_scores
ORDER BY rank
LIMIT 10;

Snowflake Output Connector

The Snowflake connector writes pipeline output to Snowflake tables via Kafka and Snowpipe.

Architecture

Feldera → Kafka → Snowpipe → Snowflake

Configuration

Write to Kafka with Snowflake-compatible format:

outputs:
  warehouse:
    stream: aggregated_results
    connector_config:
      transport:
        name: kafka_output
        config:
          bootstrap.servers: "kafka:9092"
          topic: "snowflake-ingestion"
      format:
        name: json
        config:
          update_format: "snowflake"

Snowpipe Setup

Configure Snowpipe to ingest from the Kafka topic:

CREATE PIPE my_pipe AS
COPY INTO my_table
FROM @my_stage
FILE_FORMAT = (TYPE = JSON);

Data Format

The Snowflake format produces JSON records compatible with Snowpipe:

{"user_id": 1, "count": 100, "timestamp": "2024-01-15T10:00:00Z"}
{"user_id": 2, "count": 200, "timestamp": "2024-01-15T10:01:00Z"}

Use Cases

Data warehouse loading:

CREATE MATERIALIZED VIEW daily_summary AS
SELECT 
    DATE_TRUNC('day', event_time) as day,
    user_id,
    COUNT(*) as event_count,
    SUM(amount) as total_amount
FROM events
GROUP BY day, user_id;

Real-time reporting:

CREATE MATERIALIZED VIEW hourly_metrics AS
SELECT 
    DATE_TRUNC('hour', event_time) as hour,
    metric_name,
    AVG(value) as avg_value,
    MAX(value) as max_value
FROM metrics
GROUP BY hour, metric_name;

What’s Next

Connectors OverviewNats Pubsub Connectors