AnyToFabric by Exillar

Migrate to Microsoft Fabric
Fully assessed.
Automatically converted.

Connect your legacy database or ETL estate and receive a complete migration blueprint in 3–5 days — every object scored, every pipeline mapped, your entire Fabric architecture designed before a single line moves.

Microsoft Partner
Snowflake Snowflake Partner
NASSCOM Member
Microsoft Fabric Fabric Certified
AnyToFabric Assessment
SOURCE ESTATE · Azure Synapse Dedicated SQL Pool
Fabric Readiness Score
8.4 / 10
Total Objects Assessed 8,640
Auto-Migratable (~80%) 6,912
Manual Review Required 1,728
Blueprint Ready In 3–5 days
Object Inventory & Complexity Scores
Architecture Recommendation (Lakehouse vs Warehouse)
Wave-Based Migration Roadmap
Effort & Cost Estimation
~80%
Of objects auto-migratable
on average
3–5
Days to a full migration
blueprint, not weeks
8+
Source platforms
supported
15+
Countries served across
UK, Europe, Middle East, US
The Real Problem

Migrations stall before a single line of code moves

The estate is bigger than expected, documentation is missing, and certified Fabric engineers are genuinely scarce. Most teams don't know what they're dealing with until it's too late.

82%
of enterprise data migrations miss their first go-live deadline — before a single object has been converted.
Azure Synapse Dedicated SQL Pools retirement deadline is active. No extension expected.
No documented inventory of the estate
Thousands of stored procedures, views, and ETL jobs with business logic nobody wrote down. Migrating blind.
No Fabric expertise on the team
DP-600 and DP-700 certified architects are scarce. Hiring takes months. Waiting is not an option.
Hard deadline from Microsoft
Synapse Dedicated SQL Pools are being retired. Delays mean unsupported infrastructure with no path forward.
Budget stalled without accurate estimates
Without an object inventory and complexity score, effort estimates are guesses. Approvals stall at the finance stage.
Reports break after migration
Data moves but Power BI dashboards break or get abandoned. The business loses visibility right when they need it most.
Before vs After

What changes when you run with AnyToFabric

Activity
Without AnyToFabric
With Exillar AnyToFabric
Migration Assessment
5+ weeks, manual spreadsheets
Full blueprint in 3–5 days
Architecture Design
4+ weeks, depends on scarce talent
Lakehouse / Warehouse placement in 3–5 days
Code Conversion
3+ months of manual SQL rewriting
First pass in 3–6 weeks
Data Pipelines
6+ weeks to rebuild each pipeline
Draft pipelines in 1–2 weeks
Validation
Manual spot-checks, easy to miss data drift
Parallel-run, row-level counts & aggregates
Post-Migration BI
Out of scope — dashboards break
Power BI rebuilt on migrated Fabric data
Fabric Expertise
Hire or wait — DP-600 talent is scarce
Certified DP-600 team on every engagement
Supported Platforms

Find your migration path

Select your current platform to see exactly what AnyToFabric migrates and where it lands in Microsoft Fabric.

Azure Synapse
SQL Server
Oracle
Teradata
Snowflake
PostgreSQL
IBM Db2
Netezza
Source Platform
Azure Synapse
Dedicated SQL Pools
Microsoft is retiring Synapse Dedicated SQL Pools. Migration to Fabric Warehouse is mandatory — not optional.
Full DDL extraction — tables, views, stored procedures
T-SQL conversion with Fabric-incompatible construct removal
Data pipeline migration to Data Factory
Parallel-run row-count validation before cutover
Migrates to
Fabric Warehouse
Primary target — full T-SQL parity
Data Factory Pipelines
ETL jobs converted to Fabric pipelines
Power BI
Reports rebuilt on Fabric data
Source Platform
SQL Server
On-premises and Azure SQL Server. The most common migration source — AnyToFabric has the deepest T-SQL conversion coverage for SQL Server objects.
Tables, views, stored procedures, triggers, functions
SQL Server Agent jobs toData Factory pipelines
SSIS packages converted to Fabric-native equivalents
Schema and security object migration
Migrates to
Fabric Warehouse
Native T-SQL — minimal conversion friction
Data Factory Pipelines
SSIS / Agent jobs converted
Source Platform
Oracle
PL/SQL packages, schemas, and stored procedures. Complex type mappings and Oracle-specific syntax handled by AI-assisted conversion.
PL/SQL packages and procedures toT-SQL
Oracle data types mapped to Fabric equivalents
Sequences, synonyms, and database links handled
Oracle ETL (ODI) toData Factory pipelines
Migrates to
Fabric Warehouse
AI-converted PL/SQL to T-SQL
Data Factory
ODI pipelines converted
Source Platform
Teradata
Enterprise data warehouses with BTEQ scripts and proprietary syntax. AnyToFabric handles Teradata-specific constructs other tools miss.
BTEQ and FastLoad scripts converted
Teradata-specific SQL dialect toT-SQL
TPT utilities toData Factory pipelines
Partitioning and zone map strategies remapped
Migrates to
Fabric Lakehouse
Large-scale EDW workloads on Delta
Fabric Warehouse
SQL-first reporting workloads
Source Platform
Snowflake
Snowflake SQL to Fabric T-SQL conversion, including semi-structured VARIANT data and Snowflake-specific functions.
Snowflake SQL toFabric T-SQL dialect
VARIANT / semi-structured data toDelta format
Snowpipe and Tasks toData Factory pipelines
Snowflake UDFs toFabric Spark functions
Migrates to
Fabric Lakehouse
VARIANT data toDelta tables
Fabric Warehouse
Structured SQL workloads
Source Platform
PostgreSQL
Open-source relational databases and data warehouses. Extensions, custom functions, and PostgreSQL-specific types handled.
PostgreSQL SQL toT-SQL conversion
Arrays and JSONB toFabric-compatible formats
pg_cron jobs toData Factory scheduling
Custom extensions assessed for equivalents
Migrates to
Fabric Warehouse
Relational workloads in T-SQL
Fabric Lakehouse
JSONB / arrays as Delta
Source Platform
IBM Db2
Legacy mainframe and distributed Db2 environments. IBM-specific SQL and LOB types handled with AI-assisted conversion.
Db2 SQL dialect toFabric T-SQL
LOB and XML types mapped to Fabric equivalents
Db2 stored procedures converted with AI assist
DataStage jobs toData Factory pipelines
Migrates to
Fabric Warehouse
Db2 SQL converted to T-SQL
Data Factory
DataStage pipelines converted
Source Platform
IBM Netezza
IBM Netezza / PureData appliances. Netezza SQL and zone map optimizations remapped to Fabric performance equivalents.
NZSQL dialect toFabric T-SQL
Zone maps toFabric partitioning strategies
Netezza external tables toFabric Lakehouse
Aginity workbench scripts converted
Migrates to
Fabric Lakehouse
External tables and large-scale data
Fabric Warehouse
NZSQL converted to T-SQL
ETL Pipeline Migration

Legacy pipelines become Fabric-native data flows

AnyToFabric converts your entire ETL estate — every job, script, and workflow assessed, complexity-scored, and converted to Data Factory pipelines or Spark Notebooks.

SSIS / ADF v1 SQL Server Integration Informatica / Talend Enterprise ETL Apache Airflow DAG Orchestration Python / Shell Scripts Custom Schedulers ANYTOFABRIC Engine Assess · Convert · Validate Data Factory Pipelines & activities Spark Notebooks PySpark workloads Fabric Schedules Triggers & dependencies
Accelerator Capabilities

Six defined capabilities, end to end

AnyToFabric is not a generic statement of work. Each capability is a deliverable with specific outputs your team can act on immediately.

01
Direct Source Assessment
We connect directly to your legacy platform and scan every table, stored procedure, view, function, trigger, ETL job, and dependency. Output: structured inventory with object counts, types, and schema details.
Tables & Columns · Stored Procedures · Views & Functions · ETL Jobs · Dependencies
02
Complexity Scoring
Every object scored 1–5. T-SQL compatibility analysis identifies auto-converts vs manual review. Per-object effort estimates.
1–5 Complexity Score · T-SQL Compatibility · Effort Estimate
03
Fabric Architecture Design
OneLake layout, Lakehouse vs Warehouse placement, medallion architecture mapping, workspace allocation, capacity planning.
OneLake Design · Medallion Architecture · Capacity Planning
04
Automated Code Conversion
SQL to T-SQL. ETL jobs to Data Factory pipelines and Spark Notebooks. Flags anything needing human review.
SQL to T-SQL · ETL to Data Factory · DDL Generation
05
Parallel-Run Validation
Row-level counts and aggregates compared at object level. Every table gets pass/fail with mismatch drill-down.
Row Counts · Aggregate Checks · Sign-Off
06
Post-Migration Power BI
Most migrations end with a broken reporting layer. We rebuild your Power BI dashboards and semantic models directly on migrated Fabric data. One partner from source to dashboard — no handoff gap where reports fall through.
Dashboard Rebuild · DAX Models · Semantic Layer · PL-300 Certified
How It Works

Four phases from assessment to production

A structured process that replaces months of ad-hoc migration work with a defined timeline and specific deliverables at each stage.

Step 1 of 4
01
Discovery & Assessment

Direct connection to your source platform. Full inventory of every object, complexity scoring, and a Fabric Readiness Score.

Automated2–3 days
02
Architecture Design

Medallion layer design, Lakehouse vs Warehouse placement, workspace structure, and a wave-based migration roadmap.

Expert Review1 week
03
Migration & Conversion

Automated code conversion with engineer review of flagged objects. SQL becomes T-SQL, ETL jobs become Data Factory pipelines.

Auto + AI3–5 days
04
Validation & Handover

Parallel-run row-level validation, Power BI rebuilt on Fabric, full handover with runbooks and team training.

Certified2 days
Sample Deliverables

What you receive at each stage

Migration Readiness Scorecard — Azure Synapse Dedicated SQL Pool
8.4
Fabric Readiness Score (out of 10)
80%
Objects auto-migratable
3–5
Days to full blueprint
Object Type Total Auto-Migrate Manual Review Complexity Coverage
Tables 4,200 4,116 84 Low
Views 1,860 1,674 186 Medium
Stored Procedures 1,820 1,092 728 High
ETL Pipelines 460 322 138 Medium
Functions 300 252 48 Low
Fabric Architecture Blueprint — Medallion Layout

Each source object is mapped to a Fabric target zone based on workload type, query pattern, and team capability. Structured reporting workloads go to Fabric Warehouse (T-SQL). Spark-based and semi-structured workloads go to Fabric Lakehouse (Delta).

Bronze Layer — Raw Ingestion
Raw tables (full copy)
Source schema preserved
No transformations applied
Audit watermarks
Incremental load patterns
Silver Layer — Cleaned & Conformed
Deduplication rules
Type casting & normalisation
Business key assignment
Null handling logic
Cross-source joins
Gold Layer — Business-Ready
Dimensional models
Aggregated fact tables
KPI calculation layer
Power BI semantic model
Row-level security rules
Workload Fabric Target Format Rationale
Core DW Tables Fabric Warehouse T-SQL DDL SQL-first reporting, existing BI tooling
ETL Staging Fabric Lakehouse Delta + Spark Bulk loads, Spark-native processing
Historical Archive Fabric Lakehouse Parquet / Delta Cost-effective cold storage on OneLake
Reports & Dashboards Power BI DAX / DirectLake Rebuilt semantic models on migrated data
Parallel-Run Validation Report — Wave 1
94%
Objects passed validation
5%
Minor row-count delta
1%
Flagged for review

Source and target run concurrently for 48 hours. Row counts and aggregates compared at object level. Each object receives a PASS, WARN, or FAIL status before sign-off.

dbo.FactSales
SRC: 12,847,332 TGT: 12,847,332
Pass
dbo.DimCustomer
SRC: 284,100 TGT: 284,100
Pass
dbo.FactInventory
SRC: 4,201,884 TGT: 4,201,880
Delta: 4 rows
dbo.vw_SalesAggregated
SRC: £4,821,334.00 TGT: £4,821,334.00
Pass
dbo.DimProduct
SRC: 18,922 TGT: 18,922
Pass
Why Exillar

What separates us from the other options

Your three realistic options: Exillar AnyToFabric, a large system integrator, or attempting the migration in-house. Here's what that comparison actually looks like.

Factor Exillar AnyToFabric Large System Integrator In-House Team
Microsoft Partner status Official Microsoft Partner on Fabric, Synapse, ADF Varies by firm Not applicable
DP-600 certified engineers Multiple certified on every engagement May be available, not guaranteed Scarce — months to hire
Snowflake Partner Handles Snowflake toFabric migrations Rarely both Not applicable
Power BI / post-migration BI Dashboards rebuilt as part of delivery Usually separate engagement If team has capacity
Time to assessment blueprint 3–5 days 5–8 weeks 2–4 months
Parallel-run validation Row-level, object-by-object sign-off Manual spot-checks Rarely structured
Cost structure Competitive Ahmedabad delivery model US/UK day rates Staff cost + extended timeline
Geographic coverage UK, Europe, Middle East, US Global Internal only
Migration Effort Calculator

Estimate your migration effort

Total database objects 5,000
5,000
ETL pipelines to migrate 200
200
Internal team size (FTEs) 4
4

Estimates are based on typical enterprise migration projects. Actual timelines depend on schema complexity, data volumes, and internal readiness.

Estimated Impact
Typical manual migration timeline (months)
Estimated timeline with AnyToFabric
Months saved on delivery
Objects handled automatically (~80%)
Assessment phase — full inventory with Fabric Readiness Score — delivered in 3–5 business days at fixed fee. No obligation to proceed.
Common Questions

What teams ask before they start

How long does the assessment actually take?
For most enterprise estates, a full object inventory and migration blueprint takes 3–5 business days from the point we have read access to your source platform. Larger environments with complex dependency graphs may take a few days longer. We will give you a specific estimate after the first 30-minute scoping call — not a range designed to set expectations low.
Which source platforms do you support?
Azure Synapse Dedicated SQL Pools, SQL Server (on-premises and Azure), Oracle (PL/SQL), Teradata (EDW and BTEQ), Snowflake, PostgreSQL, IBM Db2, and Netezza. If you are on a platform not listed here, ask us directly — we can assess feasibility quickly.
What does "parallel-run validation" mean in practice?
After migration, your source and target environments run simultaneously for an agreed window. We execute the same queries against both and compare row counts, aggregates, and outputs at the object level. Every table and view gets a PASS, WARN, or FAIL status. You sign off each object individually before we recommend cutover. This is not a batch go-live on trust — it is a structured sign-off process your risk team can stand behind.
How is AnyToFabric priced?
Pricing is scoped per engagement based on estate size, source platform complexity, and how many waves the migration requires. The assessment phase has a fixed fee. Full migration pricing is provided after the assessment — once we have actual object counts and complexity scores, not before. We do not quote fixed-fee migration before we understand what we are migrating.
Do you handle Power BI and reporting after the data moves?
Yes. This is one of our core advantages over migration-only tools and firms. We rebuild your Power BI dashboards and semantic models directly on the migrated Fabric data as part of the delivery. Power BI consulting is Exillar's primary service — multiple PL-300 certified team members, extensive DAX and data model experience. You get one partner from legacy source to live dashboard.
What happens to undocumented business logic in stored procedures?
We extract the full SQL body of every stored procedure and function and run it through T-SQL compatibility analysis. Objects that convert cleanly are auto-migrated. Objects with platform-specific syntax or ambiguous logic are flagged with a complexity score and a specific note on what needs manual review. Our engineers then work through the flagged list with your team — we do not pass the problem back to you unlabelled.
We are not on Synapse — are we still a fit?
Absolutely. The Synapse retirement creates the most urgent pipeline right now, but AnyToFabric was built for all enterprise migrations to Fabric. Teams on Teradata, Oracle, on-premises SQL Server, Snowflake, and PostgreSQL come to us for exactly the same reasons: no internal Fabric expertise, no accurate effort estimate, and no structured validation approach. If your estate is on any of the supported source platforms, the service applies directly.
What does the team's Fabric certification actually mean for our project?
DP-600 is the Microsoft Fabric Analytics Engineer Associate certification. It covers Fabric Lakehouse, Warehouse, OneLake, Data Factory pipelines, Spark Notebooks, and the medallion architecture — the full stack your migration lands on. Multiple team members hold this certification, which means architectural decisions are made by engineers who understand the platform from first principles, not by reading documentation for the first time on your project.
Get Started

Migration isn't hard.
Not knowing what you're migrating is.

We connect to your source platform, inventory every object, and return a Fabric Readiness Score with a wave-based migration roadmap. Fixed scope. No obligation to proceed.

Book Free Assessment Schedule a 30-min Call
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