# How Writer Keeps Its AI Infrastructure Running with Snowflake Hybrid Tables

Manifest ID: 1793024889149137424

Original source: https://medium.com/snowflake/how-writer-keeps-its-ai-infrastructure-running-with-snowflake-hybrid-tables-80f55dd652fa

## Signal Claims

### Claim 1793025386170872781 (measured)

Standard Snowflake tables experienced 45% failure rates for insertions due to lock contention.

### Claim 1793025386176753767 (measured)

P50 insertion latency dropped from 2,362ms to 154ms after switching to Hybrid Tables.

### Claim 1793025386177090331 (measured)

Write failures dropped from 45% to near zero after switching to Hybrid Tables.

### Claim 1793025386179300992 (stated)

Writer downsized the warehouse powering its ingest pipeline from medium to extra small.

### Claim 1793025386180967866 (stated)

Writer uses a Snowflake Task to incrementally copy rows from the hybrid table to a standard table.

### Claim 1793025386158896097 (stated)

Writer routes every customer request through LLM inference providers.

### Claim 1793025386160818051 (measured)

Writer's LLM tracing pipeline generates up to 600 rows per minute at peak.

### Claim 1793025386162755220 (measured)

Writer's primary traces table receives roughly 1.3 million rows per day.

### Claim 1793025386171045243 (measured)

P50 insertion latency on standard Snowflake tables reached 2,362 milliseconds.

### Claim 1793025386173712151 (stated)

Writer evaluated writing tracing data to Postgres as an alternative to Snowflake.

### Claim 1793025386174824364 (stated)

Snowflake Hybrid Tables use row-oriented storage with row-level locking.

### Claim 1793025386182950453 (stated)

Writer is considering using Hybrid Tables for high-volume API logging data.

## Brief

```json
{
  "tldr": "Writer reduced LLM tracing write failures from 45% to near-zero by migrating to Snowflake Hybrid Tables, improving P50 latency by 15x.",
  "facts": [
    {
      "label": "Peak write volume",
      "value": "600"
    },
    {
      "label": "Daily trace volume",
      "value": "1.3 million"
    },
    {
      "label": "Initial P50 insertion latency",
      "value": "2,362"
    },
    {
      "label": "Post-migration P50 latency",
      "value": "154"
    },
    {
      "label": "Initial write failure rate",
      "value": "45"
    }
  ],
  "key_insights": [
    "Writer's LLM tracing pipeline, generating 1.3 million rows daily, experienced 45% write failure rates due to lock contention on standard Snowflake tables.",
    "Writer implemented a dual-table architecture: Hybrid Tables handle high-volume API writes, while a Snowflake Task incrementally moves data to standard tables for analytical queries.",
    "The migration allowed Write to downsize its ingest pipeline warehouse from medium to extra small while maintaining performance."
  ],
  "notable_quotes": [
    {
      "text": "INSERT latency dropped ~15x: P50 went from 2,362ms to 154ms.",
      "context": "Highlights the performance improvement achieved by switching to Hybrid Tables.",
      "speaker": "Aeril Xie"
    },
    {
      "text": "Write failures went from ~45% to essentially zero",
      "context": "Demonstrates the reliability gains for the tracing pipeline.",
      "speaker": "Aeril Xie"
    }
  ],
  "why_it_matters": "The migration enabled reliable data ingestion for QA and observability without adding external infrastructure or complex ETL.",
  "key_points": [
    "Writer's LLM tracing pipeline, generating 1.3 million rows daily, experienced 45% write failure rates due to lock contention on standard Snowflake tables.",
    "Writer implemented a dual-table architecture: Hybrid Tables handle high-volume API writes, while a Snowflake Task incrementally moves data to standard tables for analytical queries.",
    "The migration allowed Write to downsize its ingest pipeline warehouse from medium to extra small while maintaining performance."
  ]
}
```