Bulk loading + COPY from S3
Stages files in S3, then runs Redshift COPY with manifests at warehouse speed. No row-by-row inserts.
Amazon Redshift ETL
Get data into Redshift. Get insights out.
ETL, ELT, real-time CDC, and Reverse ETL — all into and out of Amazon Redshift. COPY from S3, MERGE-based change data, 270+ source connectors. Predictable monthly pricing instead of consumption-based row counting.
- 270+
- Sources to Redshift
- 2-way
- In + Reverse ETL
- <1s
- CDC latency
- No
- Per-row billing
The problem
Redshift compute is metered. Your ETL bill shouldn't pile on.
Most ways into Redshift cost you twice. Consumption-priced ETL tools bill per row on top of your cluster or Serverless spend, or you hand-roll COPY scripts and Lambda glue that someone has to own and babysit. Either way, loading the warehouse becomes its own project.
Where budgets go to die
Per-row pricing punishes the workloads that justify the warehouse.
CDC pipelines, hourly SaaS syncs, large historical backfills — exactly the data you want in Redshift — are the workloads consumption-priced tools cost the most for. Etlworks bills per platform tier, not per record. Load 200 billion rows or 200 million; same monthly cost. Predictable for your CFO, painless for your data team.
Capabilities
Redshift-native, end to end.
Real-time CDC into Redshift
Log-based CDC from MySQL, Postgres, SQL Server, Oracle, Mongo, DB2 — sub-second latency, MERGE/upsert deduping via staging tables.
Reverse ETL out of Redshift
Push modeled Redshift data to Salesforce, HubSpot, Marketo, NetSuite, and 200+ SaaS targets. Same platform, same subscription.
Schema evolution
New columns and type changes propagate automatically. No DDL drift, no broken pipelines after upstream changes.
Transformations + ELT pushdown
SQL, JavaScript, Python — transform in flight or push down to run inside Redshift. dbt-friendly, dbt-optional.
Cost-aware loading
Bulk COPY, batched MERGE, and short staging windows keep cluster work efficient — on provisioned clusters or Redshift Serverless.
Patterns
Three flows, one platform.
Every Redshift data pipeline pattern, configured the same way. No separate tool for CDC, no separate tool for Reverse ETL, no COPY scripts to maintain by hand.
Source
S3
Redshift
Bulk ETL / ELT
Stage files in S3, then COPY into Redshift. The pattern AWS recommends, automated end to end.
DB Log
CDC
MERGE
CDC into Redshift
Log-based CDC streams change events into Redshift via staging and MERGE/upsert. Sub-second latency, no Kafka.
Redshift
Transform
SaaS
Reverse ETL out
Push enriched data from Redshift to Salesforce, HubSpot, Marketo, NetSuite — 200+ SaaS targets.
Pricing transparency
A typical 50M-row pipeline, three ways.
Same workload — Salesforce account changes, Postgres orders, hourly SaaS syncs into Redshift — priced under three common ETL pricing models. Numbers are approximate, based on public pricing as of 2026, and exclude Redshift compute itself.
Consumption (per-row)
~$8,000/mo
Scales linearly with row volume. Hidden surge pricing during busy months.
Credit-based
~$3,500/mo
Better, but credits expire, and peak-load tier upgrades add cost.
Etlworks (fixed tier)
$1,000/mo
Standard tier, all features, all rows. Predictable for budgets, painless for data teams.
Specifications
Redshift integration depth.
Every part of a Redshift pipeline you'd actually run — loading, CDC, and security — supported and documented.
Loading
Staging
Amazon S3 · auto-managed lifecycle · manifest files for multi-file loads
Load method
COPY for bulk · staging + MERGE/upsert for change data
File formats
CSV, JSON, Parquet, Avro · gzip
CDC & transforms
CDC into Redshift
MERGE/upsert deduping · INSERT/UPDATE/DELETE preserved · idempotent
ELT pushdown
Redshift SQL generated for in-warehouse transformations · dbt-friendly
In-flight transforms
SQL, JavaScript, Python · applied during load
Deployment, security & auth
Targets
Redshift provisioned clusters · Redshift Serverless
Authentication
Database credentials or IAM auth · IAM role for S3 COPY
Network
In-VPC connectivity · SSL · static IP allowlisting for on-prem agents
Comparing Redshift ETL tools? See Etlworks vs Fivetran, Matillion, and Airbyte
Proof
Redshift pipelines, in production.
XSOLIS processes hundreds of thousands of massive X12 messages — each tens of megabytes — converting them to JSON and Parquet and loading them into Amazon Redshift, the volume that exceeded the capacity of other tools.
XS
Read the case study
XSOLIS
High-volume load · X12 → JSON / Parquet → Redshift
FAQ
Common questions.
How does Etlworks load data into Redshift?
Etlworks stages files in Amazon S3 and runs the Redshift
COPY command to bulk-load them — the pattern AWS recommends. It does not do row-by-row INSERTs. CSV, JSON, Parquet, and Avro are supported, with manifest files for large multi-file loads.Does Etlworks support real-time CDC into Redshift?
Yes. Log-based CDC from MySQL, Postgres, SQL Server, Oracle, MongoDB, and DB2 streams change events into Redshift. Changes are applied through a staging table and MERGE/upsert so INSERT, UPDATE, and DELETE are preserved idempotently, with sub-second source latency.
How does Etlworks authenticate to Redshift?
Over the Redshift JDBC connection with database credentials or IAM-based authentication, and an IAM role for the S3 staging bucket used by
COPY. Connections run inside your VPC with SSL; works with Redshift provisioned clusters and Redshift Serverless.Can I use dbt with Etlworks and Redshift?
Yes. Etlworks loads raw data into Redshift, then you can trigger a dbt run to model it — or use Etlworks's native SQL, JavaScript, and Python transformations and skip dbt. ELT pushdown is supported, so transformations can run inside Redshift.
Will Etlworks drive up my Redshift costs?
Etlworks's loading patterns are designed to be efficient: bulk
COPY from S3 rather than chatty inserts, batched MERGE during CDC, and staging that keeps load windows short. Because Etlworks bills per platform tier — not per row — your integration cost stays flat as data volumes grow, on top of whatever Redshift compute you run.Can I migrate from Fivetran, Matillion, or Airbyte to Redshift on Etlworks?
Yes — migrations from each are common and well-documented. We provide a migration assessment for cost (typically large savings versus consumption pricing), timeline, and connector parity. Reach out via Talk to us and we'll send a migration brief specific to your current platform.
Start your trial
14 days. No card. Real workloads.
Spin up a free trial, point it at your Redshift cluster, and load production data. See what predictable ETL pricing actually feels like.