The Multi-Dimensional
Data Platform for
Analytics, Engineering & AI.

-- Cross-source federated ANSI SQL query
SELECT 
    c.region,
    date_trunc('day', o.order_timestamp) AS sale_day,
    count(DISTINCT o.order_id) AS total_orders,
    sum(o.gross_revenue) AS total_revenue,
    avg(t.telematics_latency_ms) AS avg_latency
FROM iceberg.gold.revenue_daily o
JOIN postgres.public.customers c 
    ON o.customer_id = c.id
JOIN kafka.realtime.fleet_telematics t
    ON o.dispatch_id = t.dispatch_id
WHERE o.order_timestamp >= current_date - INTERVAL '7' DAY
GROUP BY 1, 2
ORDER BY total_revenue DESC;

from dmodulus.dbutils import dbutils
from pyspark.sql import functions as F

# Native Databricks dbutils secrets compatibility
api_key = dbutils.secrets.get(scope="core_ai", key="vector_key")
s3_path = dbutils.widgets.get("target_zone")

# Distributed Spark DataFrame transformation
df = spark.read.table("iceberg.silver.customer_telemetry")
clean_df = df.filter(F.col("event_status") == "CONFIRMED")              .withColumn("modulus_score", F.abs(F.col("variance")))

clean_df.writeTo("iceberg.gold.customer_360").append()
print(f"Auto-scaled Spark: Job completed, cluster scaling to zero.")

from dmodulus.ai import RAGPipeline, EmbeddingJob

# Vectorize directly from Gold Iceberg table
pipeline = RAGPipeline(
    name="enterprise_knowledge_base",
    source_table="iceberg.gold.customer_support_docs",
    chunking={"strategy": "semantic_recursive", "chunk_size": 512},
    embedding_model="text-embedding-3-small",
    in_lake_vector_sink="iceberg.ai.vectors_customer_index"
)

# Execute distributed indexing on ephemeral Spark
job = pipeline.execute_distributed(executors=4)
print(f"Successfully indexed {job.total_chunks} vectors in-lake.")

{
  "enterprise_organization": "Global Fintech Corp",
  "workload_engine": "Tesseract Dynamic Spark & Trino",
  "underlying_instances": "AWS EC2 c6i.4xlarge (Spot)",
  "raw_cloud_cost": "$4,120.00",
  "tesseract_compute_markup": "$0.00 (0.0%)",
  "snowflake_equivalent_credits": "$18,450.00",
  "databricks_equivalent_dbu": "$16,800.00",
  "net_monthly_savings": "$14,330.00 (77.7%)"
}