Replace Fivetran + Snowflake: MySQL to S3 Parquet Analytics, Self-Hosted

Description and use

Teams replace Fivetran and Snowflake by exporting MySQL tables to Parquet in S3 and querying them with SynapCores, cutting costs on data movement and compute.

Problem

Teams often pay for two separate vendor services—an ETL tool and a cloud warehouse—to move and query operational data, incurring growing costs for data movement and compute time.

Outcome

Exporting MySQL tables to Parquet in S3 and querying them with SynapCores reduces costs by eliminating ETL row charges and warehouse compute minutes, while providing millisecond query performance comparable to DuckDB.

Workflow

• Configure SynapCores connection to MySQL
• Set destination to S3-compatible bucket
• Create export job with cron schedule (snapshot or incremental)
• Run job and verify partitions
• Register Parquet as external SQL table
• Query data with plain SQL

Evidence

The ETL tool charges for moving rows. Fivetran, for example, bills on monthly active rows — every row inserted, updated, or deleted in a synced table counts.

Source

SynapCores v2.0 added a data-lake export built into the database: A connection to your MySQL holds the credentials once… A job exports tables to Parquet on a cron schedule you set… Each run reports rows, bytes, peak memory, and exit code… The Parquet is then registered as an external SQL table and queried in place.

Source

We benchmarked SynapCores against DuckDB on the same Parquet objects in the same bucket: Scan 189,361 rows of a lake table – 10.1 ms vs 28.6 ms; Count a join across two lake tables – 5.5 ms vs 10.9 ms.

Source

With SynapCores CE on your own infrastructure: Software: $0 — the Community Edition is free. Server: one VM sized for your query load… S3 storage: about $23 per TB-month on S3 Standard.

Source