Platform overview

Lyftron is a modern data platform that expands traditional data loading (ETL) with real-time access to any data, from one place.

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.

  • Manage all connections to data sources in one place
  • Prepare data sets in a self-service data preparation portal
  • Load the data to a target Data Warehouse

Lyftron data pipeline architecture

Data sources

Source connectors

Connect to data sources and prepare the data for reading
  • Connect to data sources
  • Push down filters and transformation
  • Read filtered data

Normalized SQL data pipeline

Transforms the data like it was already in a database
  • Unify data types across data sources
  • Transform the data using SQL
  • Join across disparate data sources

Target data loaders

Maintain the target Data Warehouse and load the data
  • Automatically manage target tables
  • Choose the right data types
  • Load the data
  • Manage indexes and partitions
Target data warehouses
Business intelligence tools

Disadvantages of a traditional data warehouse

Given the length of a data pipeline, there is always a delay before the data is consumable for analytics. What if the whole data preparation process could be simplified and unnecessary delay and rework avoided?

Lyftron addresses the biggest delay in data preparation by giving access to all data sources before they are transformed and loaded:

  • Prototype the data model on real-time data
  • Cleanse and load the data later
  • Deliver insights 4x faster

Universal data platform for analytics

Lyftron is a data layer for Analytics that combines traditional data loading with Logical Data Warehousing to improve collaboration and enable early access to any data. 
The SQL interface accepts queries that are routed to either to the target Data Warehouse or executed in real-time at the data source. The data may be loaded to a  Data Warehouse later, but the time saved on early prototyping the data model is priceless.

Data management features

Data connectors

Register all data sources in one place. Use ODBC, JDBC, ADO.NET or API data sources. 

  • Source schema synchronization
  • 130+ available data connectors
  • Smart SQL push down

Data loaders

Register a target Data Warehouse and select which tables and data sets are replicated. 

  • Automatic table creation
  • Automatic data type mapping
  • High-availability data loading that maintains two copies of data and virtually switches the target table

Data preparation

Self-service data preparation for data savvy users to encourage collaboration and reuse. 

  • Data catalog with search
  • Virtual data sets and views
  • Virtual primary and foreign keys across disparate data sources that are visible in BI Tools

SQL processing features

SQL server simulation

Fully simulated SQL Server layer makes all data analyzable with T-SQL. Treat everything like an SQL Server Data Warehouse.

  • Transact-SQL emulation (parser)
  • SQL Server (TDS) protocol simulation
  • T-SQL procedural statements

Query acceleration

Accelerate slow queries by caching them in-memory or in a faster database. Build pre-aggregates that are 1000x smaller.

  • Index management
  • Pre-aggregation of big data sets with groupings and joins
  • Columnar in-memory processing

Data virtualization

Simulate a database that has real-time federated tables instead of a staging layer. Build a true Logical Data Warehouse.

  • SQL push-down
  • Cost based optimiser
  • Statistics management

Operations & management features

Processing & monitoring

Manage and data management jobs in one place. Keep the Data Warehouse healthy by detecting invalid data sets.

  • Programmable job scheduler, controlled with SQL
  • Bottom-up and top-down data lineage
  • Job monitoring

Security

Apply data security features for any data source, on-premise or cloud.

  • Row-access security
  • Dynamic data masking
  • Windows Integrated Authentication for any data source

Built-in apache spark

Simply start Lyftron, connect data sources and use a built-in Apache Spark as a Data Lake. Migrate to a bigger instance later.

  • Instant Big Data analytics without a Data Warehouse
  • Managed from Fedeza
  • In-memory partitioning and caching

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 how 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 target data warehouses

Supported data sources

You are just one click away from a modern data hub