Data Warehouse Software That Plays Nice With the Warehouse You Already Have.

No - and we don't want to be. Snowflake, Databricks, BigQuery, and Redshift are excellent warehouses, each strong on different workloads. Logiciel is the management layer around the warehouse you already have or are evaluating: ingestion, transformation orchestration, governance, observability, cost telemetry. We sit between source systems and your warehouse on the inbound, between your warehouse and BI/ML/reverse-ETL on the outbound, and across the warehouse itself for cost and reliability management. By staying out of the warehouse business, we stay neutral on the warehouse choice - which means we can honestly recommend the right warehouse for your workload, not the one that pays our highest partner tier.

No - and we tune for whichever you've standardized on. Our customer base runs roughly 50% Snowflake, 25% Databricks, 15% BigQuery, 10% Redshift, with a small Iceberg-on-S3 segment growing fast. Each warehouse wins for different patterns: Snowflake for SQL-heavy enterprise analytics, Databricks for ML-adjacent and Spark workloads, BigQuery for ad-tech-style aggregation at scale, Redshift for AWS-deep stacks. We optimize Logiciel for whichever you run, including warehouse-specific features (Snowpark, Delta Live Tables, BQ ML, Redshift ML) where they matter. We will tell you honestly when your workload would run better on a different warehouse, but we don't push migration unless the savings are material.

We can run a workload-grounded TCO analysis - taking your top 50-100 actual queries and benchmarking them on Snowflake, Databricks, BigQuery, and Redshift with realistic compute sizing. Output is an honest TCO comparison (compute, storage, egress, operational lift) and a capability-fit assessment. About half of customers who consider switching end up staying - the perceived savings don't survive workload analysis once the migration cost and operational disruption are factored in. The other half migrate, and Logiciel runs the migration with parity testing so reports match cent-for-cent across the cutover. Many customers stay multi-warehouse permanently for different workload classes.

Drop-in. We add lineage, testing, observability, and cost telemetry without changing your dbt project structure or how your team writes SQL. Logiciel orchestrates dbt runs natively (no Airflow shim required), surfaces dbt tests in a unified pipeline view, and extends dbt's column-level lineage into upstream ingestion and downstream BI. dbt Cloud customers can keep dbt Cloud for development workflows and use Logiciel for production orchestration; dbt Core customers get a managed dbt runtime included. About 80% of our customer base runs dbt - we treat it as a first-class citizen, not a workaround.

We complement them, never compete. Snowflake's compute, storage, security, and SQL engine are excellent - Logiciel doesn't try to replicate any of that. We provide the connective tissue Snowflake doesn't: source-system ingestion (Fivetran-class), pipeline orchestration (Airflow-class), observability (Monte Carlo-class), governance (Atlan-class), cost telemetry (Select-class), and feature stores (Tecton-class) - unified into one platform. For Snowflake-heavy customers, Logiciel typically replaces 4-6 point tools surrounding the warehouse, lowering total TCO 30-50% while improving operational clarity. Snowflake's own ecosystem (Snowpark, Cortex, Streamlit) is fully supported and we lean on it where appropriate.

Both - pricing tiers and feature scope flex to the size of your data team. Mid-market customers (5-30 data engineers, 50-200 pipelines) typically pay $30-80K ARR for the full platform with self-serve onboarding. Enterprise customers (50+ data engineers, multi-BU, regulated) start around $150K ARR and scale up with dedicated TAM, advanced governance, custom SLAs, and US-citizen engineering pools. The platform is the same; what flexes is the support model and the governance depth. Customers often start mid-market and upgrade to enterprise as their footprint grows - we don't gate core capability behind enterprise tier the way some competitors do.

Limited - we focus on cloud warehouses (Snowflake, Databricks, BigQuery, Redshift) but can integrate with on-prem Teradata, Vertica, Netezza, Oracle Exadata, and SQL Server during a migration period. Most on-prem warehouse customers come to us specifically because they're modernizing - running parallel for 6-18 months while Logiciel manages both the legacy on-prem warehouse and the cloud target, with parity testing across reports. After cutover, we retire the on-prem connection. We don't recommend Logiciel for customers planning to stay fully on-prem indefinitely; the value proposition is strongest in cloud and hybrid scenarios.