From Redshift to the Future: Unlocking the Intelligent Lakehouse for Agentic AI
Get started today: https://www.dremio.com/unlock-ai-and-analytics-escape-redshifts-limitations/ Struggling with Amazon Redshift's rising costs, query latency, and AI readiness challenges? Join this comprehensive webinar as data teams discover why they're migrating to Dremio's intelligent lakehouse platform for agentic AI workloads and modern analytics. In this detailed webinar, Alex Merced (Head of DevRel at Dremio & co-author of "Apache Iceberg: The Definitive Guide") reveals why companies are leaving Redshift and how Dremio's lakehouse architecture delivers 50-75% cost savings while enabling AI-ready data infrastructure. 🔑 Webinar Highlights: Why Companies Leave Redshift: - Query performance degradation as data and users scale - Complex ETL pipelines delaying fresh data by hours or days - Manual tuning overhead (vacuuming, keys, workload management) - Fragmented data across multiple systems with no unified view - Limited AI integration and weak semantic layer for agentic workloads - Expensive per-node pricing forcing over-provisioning - Storage costs 80-90% higher than cloud object storage (S3/ADLS/GCS) Business & Technical Benefits of Migration: ✅ Faster business insights with reduced query latency ✅ Native support for agentic AI workloads and LLM integration ✅ Simplified manageability—no cluster tuning or vacuum maintenance ✅ True elastic scalability with pay-as-you-go compute ✅ 50-75% lower total cost of ownership vs Redshift ✅ Query data directly in your data lake (Apache Iceberg format) ✅ Unified analytics across all data types with robust governance Complete Migration Framework: 1️⃣ Migration scoping and strategy selection 2️⃣ Schema migration techniques 3️⃣ Data migration options (UNLOAD, CTAS, Copy Into) 4️⃣ BI tool migration (Tableau, Power BI via Arrow Flight SQL) 5️⃣ Application connectivity updates (ODBC/JDBC) 6️⃣ Permission and governance alignment Migration Methods Demonstrated: - Direct lakehouse querying for existing Parquet files - CTAS (Create Table As) for Iceberg table creation - Redshift UNLOAD for efficient data export - Dremio UI direct connection to Redshift sources - Copy Into for incremental data ingestion - Dremio migration script library for automation Ideal for: Data engineers, data architects, analytics engineers, cloud data warehouse administrators, CDOs, and technical decision-makers evaluating modern lakehouse alternatives to Amazon Redshift. About the Speaker: Alex Merced leads Developer Relations at Dremio and co-authored O'Reilly's "Apache Iceberg: The Definitive Guide." He's spoken at Data Day Texas, Data Council, and hosts the Datanation podcast. With experience spanning development, instruction, and open-source contributions, Alex brings practical expertise to data lakehouse architecture and migration strategies. Useful Resources: 🔗 Dremio Migration Guide: https://www.dremio.com/blog/migration-guide-for-apache-iceberg-lakehouses/ 🔗 Schedule a Migration Assessment: https://www.dremio.com/unlock-ai-and-analytics-escape-redshifts-limitations/ Hashtags: #Dremio #RedshiftMigration #DataLakehouse #ApacheIceberg #AgenticAI #DataMigration #CloudDataWarehouse #DataEngineering #AnalyticsEngineering #AWSRedshift #DataArchitecture #AIReadyData #ModernDataStack #DataCostOptimization #ArrowFlightSQL #Webinar