JarvisX Capabilities

Supported stacks, conversion coverage, and quality layers across all modules.

🛡️

JarvisX means Trust & Value

We don't just wrap AI and call it conversion. Every artifact passes through a 13-layer quality engine — from deterministic rewrites and dialect-specific cards to syntax validation and auto-repair. With 91 pair-specific conversion cards, 20 deterministic rewrite rules, and sqlglot-powered syntax validation across 16 dialects, JarvisX delivers conversion accuracy that's genuinely above market — not just AI-generated output, but engineered accuracy you can trust for production migrations.

JarvisQuery (SQL Conversion)

61 pair-specific cards with function-level mappings

Sources

TeradataOracleMySQLPostgreSQLSQL ServerHiveRedshiftSnowflakeBigQuerySparkDruid

→

Targets

BigQuerySnowflakeDatabricksRedshiftPostgreSQLHiveOracleSparkSQL ServerDuckDB

Any source × any target works. Pairs with dedicated cards get function-level guidance (DATEDIFF, QUALIFY, NVL, etc.).

JarvisFlow (Workflow / ETL Conversion)

30 pair-specific cards with component-level mappings

Sources

TalendInformaticaSSISDataStageAirflowDagsterPrefectADFStep FunctionsNiFi

→

Targets

Databricks NotebookAirflowDatabricks JobsdbtADFDagsterPrefect

Talend→Databricks has 30+ component mappings (tMap, tDBInput, tRunJob, tJava, etc.).

JarvisCode (Script / Language Conversion)

Cross-language conversion with framework awareness

Sources

PythonJavaScalaShell/BashBTEQC#RubyGoJavaScriptTypeScript

→

Targets

PythonPySparkScalaJavaJavaScriptTypeScriptGoShell

JarvisSchema (DDL Rewrite)

Schema conversion with type mapping and constraint preservation

TeradataOracleMySQLPostgreSQLSQL ServerHiveRedshiftBigQuerySnowflakeDatabricksSpark

Handles: CREATE TABLE, INDEX, VIEW, constraints (PK/FK/CHECK), partitioning, identity columns, computed columns.

JarvisRisk (Migration Risk Assessment)

Source-first risk analysis with optional gap analysis

Complexity scoringVendor lock-in detectionPerformance risks Data precisionDate/time risksSecurity flags Transaction modelSchema compatibilityGap analysis

30+ risk patterns detected. 13 hard-feature detectors. Per-artifact confidence scoring with manual review flags. Optional gap analysis when converted artifacts are provided.

JarvisGraph (Lineage & Impact)

Visual lineage with risk overlay

Cross-system dependenciesUpstream / Downstream Interactive visualizationRisk-flagged columns SVG / JSON / ZIP export

JarvisData (Synthetic Test Data)

AI-powered sample data generation from DDLs

BigQuerySnowflakeDatabricksPostgreSQL

BasicRealisticAI-Enhanced 1K (2×) / 10K (5×) / 100K (15×) rows per table

13-Layer Quality Engine

Every conversion passes through these layers — beyond raw AI.

00 sqlglot deterministic transpilation (16 dialects)

01 Pre-LLM deterministic rewrites (20 rules)

02 Complexity-adaptive prompting

03 Feature detection + micro-cards

04 91 pair-specific conversion cards

05 RAG retrieval (HyDE + RRF reranking)

06 LLM conversion (Advanced AI Agent)

07 Post-LLM deterministic rewrites

08 Syntax validation (sqlglot, 16 dialects)

09 Category-specific validation

10 Auto-repair (single-pass LLM fix)

11 Semantic scoring (sampled)

12 Confidence scoring + review flags

Featured Conversion Pairs (with dedicated cards)

These pairs have the deepest function-level guidance. All other pairs work via base cards + LLM knowledge.

JarvisQuery (61 pairs)

Teradata → BigQuery ★
Teradata → Snowflake ★
Teradata → Redshift
Teradata → Spark
Teradata → PostgreSQL
Oracle → BigQuery
Oracle → Snowflake
Oracle → PostgreSQL
Oracle → Redshift
Oracle → Spark
MySQL → BigQuery
MySQL → Snowflake
MySQL → Redshift
MySQL → PostgreSQL
MySQL → Spark
MySQL → DuckDB
PostgreSQL → BigQuery
PostgreSQL → Snowflake
PostgreSQL → Redshift
SQL Server → BigQuery
SQL Server → Snowflake
SQL Server → PostgreSQL
Hive → BigQuery
Hive → Spark
Redshift → BigQuery
Redshift → Snowflake
Snowflake → BigQuery
BigQuery → Snowflake
Spark → BigQuery
Druid → BigQuery
... and 31 more pairs

JarvisFlow (30 pairs)

Talend → Databricks Notebook ★
Talend → Airflow ★
Talend → Databricks Jobs
Talend → dbt
Talend → ADF
Informatica → Databricks Notebook ★
Informatica → Airflow
SSIS → Databricks Notebook ★
SSIS → Airflow
DataStage → Databricks Notebook
Airflow → Databricks Jobs
Airflow → Dagster
Airflow → Prefect
ADF → Airflow
ADF → Databricks Jobs
Dagster → Airflow
Dagster → Prefect
Prefect → Airflow
Step Functions → Airflow
dbt → BigQuery
dbt → Snowflake
... and 9 more pairs

JarvisCode

Any → Any supported
10 source languages
8 target languages
80 possible combinations

Highlighted:
Python → PySpark
Java → Python
Scala → Python
BTEQ → Python
Shell → Python
C# → Python
JavaScript → TypeScript
TypeScript → JavaScript

Pair-Specific Cards

11+

SQL Dialects

ETL/Workflow Tools

Programming Languages

Quality Layers

Deterministic Rewrite Rules