Built for Google Cloud databases.

Source and target

Cloud Spanner

Move into Spanner at full instance throughput.

Wirekite Data loads Spanner through its fastest native write path — filling whatever throughput the instance has, with no trickle of single-row inserts. For ongoing sync, it captures changes straight out of Spanner into the warehouse of your choice.

• Fills the instance's available throughput — no capacity left idle.
• Large tables spread across nodes from the first batch, so no single table bottlenecks the load.
• Works both ways — bulk-load into Spanner, or stream its changes out for analytics.
• Safe to re-run: a repeat pass reconciles without duplicating data.

Target

BigQuery

Bulk-load fast. Keep it in sync.

Wirekite stages your data in your own Google Cloud Storage, then lands it in BigQuery through its fastest bulk path. For change streams, it keeps the dataset current — applying inserts, updates, and deletes in the order they happened.

• Scoped, least-privilege access — no project-wide permissions.
• One connection serves many datasets; pick the target per migration.
• Type-aware across source dialects: timestamps, NUMERIC precision, JSON, and NULL handling land correctly.
• Connection and storage access are checked up front, so credential errors surface before a migration starts, not during it.

Source and target

AlloyDB for PostgreSQL

A drop-in Postgres target.

AlloyDB speaks Postgres, so Wirekite drives it with the same battle-tested path that sustains 1.2 billion changes an hour on Postgres — fast on both the load and the change-capture side.

• The same engine class we publish 1.2B changes/hour on, sustained.
• Loads at AlloyDB's full write throughput.
• The natural destination for an Oracle → AlloyDB move — the most common cloud migration we run.
• Validate proves the move row by row afterward, with type-aware comparison.

Source and target

Cloud SQL for MySQL

Cloud SQL MySQL, both directions.

Wirekite drives Cloud SQL MySQL exactly the way it drives self-hosted MySQL — capturing changes at the source's full rate and landing data through the target's fastest native load path.

• Capture saturates CPU, disk, and network at once.
• Lands through the database's fastest bulk path, not one row at a time.
• The same source path that moves ten million MySQL changes into Firebolt in 53 seconds on real hardware.
• First-class for the Cloud SQL → BigQuery analytics pipeline.

Source and target

Cloud SQL for PostgreSQL

Cloud SQL Postgres, both directions.

Cloud SQL Postgres takes the same fast Postgres path as AlloyDB and self-hosted Postgres — Wirekite captures changes with no single-stream ceiling and lands bulk data at the target's full throughput.

• Change capture with no single-stream ceiling.
• End-to-end Postgres → Postgres measured at 307K row changes per second, with every change applied.
• Bulk extract and load both run at the target's full throughput.
• Combine with Validate to prove the move row by row before flipping traffic.