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Data Integration & Migration

Amazon Redshift Development and Consulting Services

The AWS environment and modern third-party tools (AWS Glue, Amazon Data Firehose, Redshift streaming ingestion, zero-ETL integrations, S3 auto-copy, dbt, Fivetran, Airbyte, Matillion, Etleap) provide exceptional performance and scalability for loading data into Redshift. The key to a successful Redshift data warehouse implementation is to choose the right data loading strategy for each source: most 2026 pipelines need far less custom ETL code than they did five years ago, and a good part of our work is removing pipelines rather than writing them. Our Redshift consultants maintain extensive experience building scalable data integration solutions that include:

  • Zero-ETL integrations from Aurora MySQL, Aurora PostgreSQL, RDS and DynamoDB into Redshift, with table filtering, lag monitoring and cost review
  • S3 auto-copy jobs (COPY JOB) that load new files as they land, replacing scheduled COPY scripts
  • Preparation of data in S3 (Parquet, partition layout, file sizing) and bulk loading with the Redshift COPY command
  • Streaming ingestion from Kinesis Data Streams and Amazon MSK using materialized views, and Amazon Data Firehose delivery where buffering to S3 is preferable
  • AWS Glue and Amazon MWAA (Apache Airflow) for orchestrated batch transformations; dbt for the in-warehouse modeling layer
  • Migration of existing data warehouses from Snowflake, Google BigQuery, Databricks, Teradata and Oracle to Redshift
  • Migration of operational databases (PostgreSQL, MySQL, Microsoft SQL Server, Oracle) and SaaS sources (Salesforce, HubSpot, Stripe and similar) into Redshift
  • Legacy RDBMS migrations: DB2 (LUW, AS/400, iSeries, z/OS), Informix, InterBase, Firebird, Progress and Sybase (ASA, ASE, IQ) via AWS DMS or custom extraction
  • Implementation of incremental updates to the data model in Redshift to improve data load times
  • Normalization and validation of data during the load process
  • Detailed migration plan blueprint, including cutover and parallel-run strategy
  • JSON schema definitions to map S3 data to Redshift tables and columns
  • PgBouncer connection pooling between PostgreSQL applications and Redshift
  • Work closely with key stakeholders at the client to ensure a smooth migration strategy

See our dedicated Zero-ETL & Real-Time Ingestion service page for the real-time side of this work.

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