Posts - Page 29

All the articles I've posted, page 29.

• 13 MIN READ•May 24, 2026

  Designing Governed RAG on Data Products

  Design enterprise RAG on governed data products: enforce access policies at retrieval, route numeric questions through a semantic layer, and keep audit trails.

  Governed Rag Enterprise Data ProductsEnterprise Rag ArchitectureGoverned Retrieval Augmented Generation
• 12 MIN READ•May 24, 2026

  What Iceberg V3 Advances Mean for CDC Pipelines

  Apache Iceberg V3 brings deletion vectors and row lineage that reshape CDC pipeline design. Learn what these features mean for your streaming data architecture.

  Iceberg Cdc PipelineIceberg Deletion VectorsIceberg Row Lineage
• 13 MIN READ•May 24, 2026

  Kafka 4.0 Changes Streaming Platform Operations

  Kafka 4.0 removes ZooKeeper and ships KRaft and KIP-848 by default. Learn what those changes mean for platform operations, upgrades, and client configurations.

  Kafka 4.0 UpgradeKafka KraftZookeeper Removal Kafka
• 13 MIN READ•May 24, 2026

  Lance and Iceberg for Multimodal AI Data

  LanceDB and Apache Iceberg serve complementary roles in a multimodal AI lakehouse. Learn when to use Lance for embeddings and random access, and Iceberg.

  Lancedb Iceberg Multimodal Ai DataLancedb FormatLance Vs Iceberg
• 13 MIN READ•May 24, 2026

  Bringing MLflow and Data Pipelines Closer Together

  How MLflow 3 connects ML experiments to data pipelines: training data lineage, input quality checks, model vs. data drift, CI/CD, and scheduling with Airflow.

  Mlflow Data Pipeline ObservabilityMlflow 3 Genai TracingMlflow Data Quality Monitoring
• 14 MIN READ•May 24, 2026

  Modern Feature Stores Beyond Batch Pipelines

  Feature stores like Feast now support streaming feature views from Kafka and Kinesis alongside batch pipelines.

  Feature Store Streaming Real-Time MlFeast Streaming FeaturesOnline Offline Feature Store
• 12 MIN READ•May 24, 2026

  OpenLineage as the Spine of Data Observability

  How OpenLineage collects lineage from Airflow, Spark, Flink, and dbt, and how to use it for blast radius analysis, SLA tracking, and Marquez or DataHub.

  Openlineage Data ObservabilityOpenlineage AirflowOpenlineage Spark
• 25 MIN READ•May 24, 2026

  When Paimon Beats Iceberg for Mutable Streams

  Paimon's LSM-tree upserts vs Iceberg v3 deletion vectors for high-churn CDC streams: write cost, read cost, compaction, and when to pick each.

  Apache Paimon Mutable StreamsPaimon Vs IcebergCdc Streaming Lakehouse
• 13 MIN READ•May 24, 2026

  Policy as Code for Lakehouse Governance

  Policy as code for the lakehouse: OPA, ABAC, row filters, and column masks across Databricks, Snowflake Horizon, and BigQuery, plus CI/CD for your policies.

  Policy As Code Data Governance LakehouseOpa Rego LakehouseAbac Databricks
• 11 MIN READ•May 24, 2026

  Real-Time Lakehouse Patterns with Apache Flink and Iceberg

  Learn how to build a real-time lakehouse with Apache Flink 2.1 and the Dynamic Iceberg Sink, covering schema evolution, exactly-once delivery, and compaction.

  Real-Time Lakehouse FlinkFlink Iceberg SinkKafka To Iceberg
• 14 MIN READ•May 24, 2026

  Choosing Vector Stores for Retrieval Workloads

  pgvector, Milvus, Weaviate, and LanceDB each make different tradeoffs on index type, hybrid search, scale, and operational complexity.

  Vector Store Comparison Retrieval WorkloadsPgvector HnswMilvus Hybrid Search
• 24 MIN READ•May 23, 2026

  Single-Node Data Engineering: DuckDB, DataFusion, Polars, and LakeSail

  Optimize single-node data engineering with DuckDB, DataFusion, Polars, and LakeSail. Compare architectures and learn when to transition to Dremio MPP.

  DuckDBApache ArrowDataFusion