Feed your data lake with AI-ready tables for 30-50% lower cost
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Confluent's Tableflow converts Apache Kafka topics directly into analytics-ready tables in Apache Iceberg and Delta Lake formats, eliminating the need for separate sink connectors, ETL jobs, and post-landing compute. By reusing Kafka segments stored in Confluent's Kora engine and converting them to Parquet, Tableflow removes egress charges, reduces Kafka topic storage costs by 67% (no 3x replication), and bundles compaction and schema evolution into a single per-topic-hour fee. Benchmarks against Snowflake Snowpipe, Databricks Delta Live Tables, Amazon S3 Tables, and custom ETL pipelines show 30–50% lower total ingestion costs. A medium-throughput example (10 topics, 1 MBps, 7-day retention) shows monthly costs of ~$2,555 with Tableflow versus $5,063–$6,075 with traditional stacks. Additional benefits include vendor-neutral open table formats, bring-your-own-storage, near-real-time freshness, and shift-left processing via Apache Flink integration. Tiered pricing with up to 90% discounts at scale is announced for later in the month.
Table of contents
The Hidden Cost of Feeding Your Lake or LakehouseTableflow: Turn Apache Kafka ® Topics into Analytics‑Ready Tables4 Drivers of the 30%–50% SavingsReal‑World Benchmarks vs Common AlternativesArchitectural and Operational Benefits Beyond CostWhen You’ll See the Biggest Return on InvestmentPricing That Automatically Scales as You ScaleGetting StartedSort: