Platform overview

Lyftron is a modern data platform that expands traditional data loading (ETL) with real-time access to any data, from one place. Lyftron's value propositions that make it apart from traditional ETL/ELT platforms for modern data warehouse modernization & migration

A single data platform to

Data preparation for analytics with Lyftron

The data that is located in various data sources is not always usable for analytics without preparation and loading to a central Data Warehouse. Lyftron manages a Data Pipeline that unifies all data sources to a single format and loads the data to a target Data Warehouse, which is used by BI tools.

Lyftron’s unique feature is a Normalized SQL Data Pipeline in the middle of the data transformation process. All data sources are virtually treated like SQL databases and are transformed by defining virtual data sets and views.

Time to Insight shorter by 75%

The data that is located in various data sources is not always usable for analytics without preparation and loading to a central Data Warehouse. Lyftron manages a Data Pipeline that unifies all data sources to a single format and loads the data to a target Data Warehouse, which is used by BI tools.

Lyftron’s unique feature is a Normalized SQL Data Pipeline in the middle of the data transformation process. All data sources are virtually treated like SQL databases and are transformed by defining virtual data sets and views.

Migration of legacy data warehouse to modern cloud data warehouse

Lyftron Data Hub works as a pass-through SQL proxy to multiple databases and data sources. Both the legacy DW and Snowflake are connected to Lyftron, BI tools are switched to use Lyftron as a data source. Lyftron accepts SQL queries, translates them and forwards them (pushes down) to the legacy data ware-house or Snowflake.

As a result, the data warehouse may be migrated step-by-step. This particular feature is mostly important for migrations from Microsoft SQL Server because Lyftron is wire compatible with MSSQL and only the server name must be changed in BI tools from MSSQL to Lyftron.

Whole database migration
(lyft-and-shift approach) is possible in 10 days, independent of the database size (number of tables)

All data pipelines in Lyftron are defined in SQL. This concept enables scripting all data pipelines. This solution is a huge advantage over ETL tools, because data pipelines may be automatically scripted instead of building them manually in a visual designer. 

A lot of data warehouse architects are looking for a way to apply DevOps principles in the data warehouse design and automate as much as possible via scripting.

Large table scan queries on modern cloud data warehouse may be 1000x faster

When Lyftron is used as an SQL proxy that translates SQL queries on the fly. This feature is used when a cube is defined in Lyftron. Aggregated queries with GROUP BY and joins are rewritten on the fly to use smaller, preaggregated materialized views. Lyftron maintains materialized views for frequently queried combinations of joins and grouping conditions. An example: the main dashboard may always show a graph with the revenue per business unit and such query would have to perform a full table scan for a huge fact table whenever a user opens the main dashboards. With Lyftron, it is possible to define a preaggregated view with a GROUP BY bu_id that has only 20 rows. Those queries will execute instantly because they are redirected to a smaller materialized view.

Modern cloud database is usable from all BI tools

Lyftron works as an SQL proxy (a semantic data layer) between BI tools and Snowflake. Lyftron is wire compatible with Microsoft SQL Server and uses Transact-SQL dialect. MSSQL drivers are widely supported by all BI tools on the market. Business users could even connect directly from Microsoft Excel to Snowflake through Lyftron, without installing any ODBC drivers, because SQL Server drivers are already preinstalled on Windows.

Windows active directory authentication for
Modern cloud data wareouse possible from any BI tool

When Lyftron is used as an SQL proxy that translates SQL queries on the fly. This feature is used when a cube is defined in Lyftron. Aggregated queries with GROUP BY and joins are rewritten on the fly to use smaller, preaggregated materialized views. Lyftron maintains materialized views for frequently queried combinations of joins and grouping conditions. An example: the main dashboard may always show a graph with the revenue per business unit and such query would have to perform a full table scan for a huge fact table whenever a user opens the main dashboards. With Lyftron, it is possible to define a preaggregated view with a GROUP BY bu_id that has only 20 rows. Those queries will execute instantly because they are redirected to a smaller materialized view.

Lyftron data pipeline architecture

Learn how Lyftron can help

Business Intelligence Acceleration

Learn how a combination of a data pipeline with a Logical Data Warehouse shortens Business Intelligence projects 4x.

Business Intelligence Acceleration

Build a Logical Data Warehouse across data sources. Let analysts find, define and share data sets. Combine replicated and real-time data.

Data Warehouse Modernization

Learn how to smoothly migrate to a new data warehouse and also change the way users are finding and accessing data.

Data Warehouse Modernization

Move to a new Data Warehouse step-by-step. Create a modern Data Hub for Analytics that shortens the time to insights.

Hybrid Cloud Data Warehousing

Learn how to overcome the challenges of Hybrid Cloud connectivity across Data Warehouses, data sources and SaaS BI tools.

Hybrid Cloud Data Warehousing

Lyftron simulates SQL Server and will serve as a bridge for SaaS BI tools. Manage all data in one place and replicate to the Cloud when needed.

Supported data sources

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