Sathus AI 2.0 is now generally available — evaluation harnesses and guardrails included. Explore
Explore 300+ production architecture guides, streaming pipelines, open table format benchmarks, and validated healthcare compliance frameworks engineered by Sathus Principal Architects.
Each pillar contains authoritative architecture guides, real-time code blueprints, and direct links to Sathus enterprise services.
Governed Medallion Lakehouses, Streaming Pipelines & Data Reliability
Production-grade data pipelines, Delta Lake and Apache Iceberg architectures, Change Data Capture (CDC), zero-loss streaming, and enterprise data quality governance.
High-Throughput Spark Clusters, Flink Stream Processing & Memory Optimization
Distributed computing architecture, Apache Spark and PySpark performance tuning, shuffle optimization, Apache Flink stateful streams, and Kafka cluster topology.
Sub-Second Analytical Dashboards, Semantic Layers & Dimensional Modeling
Cloud data warehouse architecture across Snowflake, BigQuery, and ClickHouse, Kimball dimensional modeling, unified semantic layers, and embedded SaaS analytics.
Enterprise Databricks Unity Catalog, ADF, Synapse & Multi-Cloud Infrastructure
Production cloud data architectures on AWS and Azure, Databricks Unity Catalog governance, Auto Loader ingestion, private endpoints, and Terraform infrastructure as code.
Streaming FHIR R4 Lakehouses, HIPAA Compliance & Clinical NLP Pipelines
HIPAA-compliant healthcare data platforms, FHIR R4 / HL7 v2 real-time streaming, Master Patient Index (MPI) probabilistic record linkage, OMOP CDM harmonization, and PHI de-identification.
FDA 21 CFR Part 11 Validated Lakehouses, Multi-Omics & CDISC Automation
Validated cloud data platforms for biopharma, CDISC SDTM/ADaM pipeline automation, multi-omics data integration, VCF variant processing, and GxP immutable audit trail engineering.
Enterprise Semantic Graphs, GraphRAG & Entity Disambiguation
Semantic data architecture, domain ontology engineering with OWL/SKOS, GraphRAG combining vector databases with Neo4j/Neptune, entity resolution, and biomedical terminology integration.
High-Accuracy Medical OCR, LayoutLM Extraction & Regulatory Document AI
Intelligent Document Processing (IDP), multi-column table extraction from complex scientific and medical PDFs, LayoutLM and vision LLMs, eCTD regulatory parsing, and automated PHI redaction.
Production Code Blueprints, Reference Architectures & Technical Glossaries
Deep dive technology profiles (Databricks, Spark, AWS, Azure, Kafka, dbt), end-to-end architecture diagrams, production implementation templates, and comprehensive technical glossaries.
An enterprise engineering guide to architecting Bronze (raw append-only), Silver (cleaned & enriched), and Gold (business aggregates) data layers using Delta Lake and Apache Iceberg.
A deep-dive technical comparison of the three dominant open-source table formats: metadata architectures, ACID guarantees, partition evolution, engine ecosystem support, and write/read latency benchmarks.
The definitive engineering triage guide to diagnosing and fixing Apache Spark OutOfMemory (OOM) crashes. Demystifying driver heap exhaustion from collect() vs executor container kills (Exit code 137), broadcast hash join thresholds, shuffle skew, Adaptive Query Execution (AQE), and off-heap memory overhead.
Complete guide to demystifying the Spark Memory Pool. How unified memory management allocates between storage and execution, how to tune off-heap memory, and how to eliminate disk spills.
The definitive engineering guide to distributed join optimization in Apache Spark 3.5. Learn how physical join selection works under the Catalyst optimizer, how to eliminate disk spills and OOMs, and how to remediate severe data skew using Adaptive Query Execution (AQE) and key salting.
Step-by-step architectural guide to deploying Databricks Unity Catalog across AWS and Azure workspaces. Covers 3-tier namespace (Catalog.Schema.Table), automated column-level lineage, SCIM identity federation, and dynamic row-level security.
Every guide in the Sathus Engineering Hub is authored and reviewed by lead data platform engineers, certified Databricks architects, and healthcare informatics specialists with active production deployments across petabyte-scale lakehouses, FDA 21 CFR Part 11 platforms, and high-concurrency streaming pipelines.
