Lyftron Data Pipeline manages connections to data sources and loads data to Azure Sql Data Warehouse . All transformations are defined in standard SQL and pushed down to data sources and Azure Sql Data Warehouse . Lyftron eliminates traditional ETL/ELT bottlenecks with automatic data pipeline and make data instantly accessible to BI user with the modern cloud compute of Spark & Snowflake.
Lyftron connectors automatically convert any source into normalized, ready-to-query relational format and provide search capability on your enterprise data catalog. Lyftron shortens data preparation activities by letting data teams create logical data sets first, evaluate the data and delay the data loading until the data sets are verified or data loading is required.
Automatically Manage Tables
Lyftron creates target tables in Azure Sql Data Warehouse and picks the right data types.
Transform with SQL
Transform or filter the data using SQL that is pushed down to Azure Sql Data Warehouse. Enable a true Extract-Load-Transform to avoid extra data copies.
Prototype Data Sets
Avoid needless delay in data preparation. Define virtual data sets on source data. Verify and load to Azure Sql Data Warehouse when required.
Columnar data pipeline
High-performance modern Data Warehouses are all columnar and efficiently process data in bulk. Lyftron extends the columnar processing to the data pipeline, which speeds up data loading and transformation.
SQL interface
Fully simulated Transact-SQL interface (wire compatible with SQL Server) enables bridged queries to any data source or target Data Warehouse. No drivers or new skills are needed to run queries on any data.
Global data catalog
Categorize all data sets stored in the Cloud, essential data sources and valuable data sets defined by data analysts and data scientists.
Expand Analytical Capabilities
Go beyond the limitations of data replication and democratize the data management. Add a Logical Data Warehouse across data sources and Azure Sql Data Warehouse. Let data users define virtual data sets from data sources and tables loaded to Azure Sql Data Warehouse.
Lyftron Logical Data Warehouse
Migrate step-by-step
Migration to Azure Sql Data Warehouse may not be possible in one step. Connect legacy data warehouses as data sources and use the SQL Interface to access data from all data warehouses, also not migrated yet.
Use any BI Tool
Lyftron fully simulates SQL Server on the wire so you can use standard SQL Server drivers available in all BI tools and query Azure Sql Data Warehouse or combine it with other data sources.
Pre-aggregate data
Define virtual data marts with aggregations, groupings and joins. Lyftron will materialize pre-aggregated views. Avoid full table scans of fact tables and let Lyftron use pre-aggregates that are 1000x smaller.
Create a data catalog
Democratize data access and let data users define data sets, describe them in the data catalog and share with others.
Apply transparent security
Transparently apply dynamic data masking, row access security or pseudonymization of data. Secure access to any data with Windows Integrated Security.
Join with any source
Join data between Azure Sql Data Warehouse and other data sources in real-time. Replicate data from other data sources only when it is required for performance reasons.
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