The Next-Gen modern data hub

Accelerate your time to trusted data with the 21st-century Lyftrondata hub. Do more with your data, get centralized control of ownership and sharing, move data at the right latency via a high-performance data pipeline, and get the finest control of your data management and operations.

Creating a centralized data hub

Lyftrondata is a Data Hub for analytics that is a central place to find all data, create shared data sets and manage data replication to a Data Warehouse in one place. 

Lyftrondata is a central data hub for analytics that aggregates all source and target databases in one place. Lyftrondata is not just yet another ETL tool that loads data to another database. Lyftrondata’s architecture goes beyond and enables real-time SQL queries to data sources by simulating a database.

Eliminate the complexity with Lyftrondata's simplicity

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Lyftrondata pipes professional architecture

Our uniqueness

  • Automatic ANSI SQL Pipeline

  • Analyze data instantly with BI and ML tools

  • Our connectors automatically normalized the data from API, Json and XML formats

  • Real-time sync, data catalog, data lineage and data governance

  • Innovative Data Sharing & Unlimited cloud compute

What you get

Query API data with SQL familiar syntax

With Lyftrondata, avoid creating time-consuming code and use your very own SQL to query any data, both structured and semi-structured. Its modern data architecture supports automatic zero code JSON/XML/API parsing to relational format. Analyze instantly with ANSI and make your data lake work for you. Lyftrondata's emulation of Microsoft SQL Server allows any client supporting connectivity to SQL Server to connect to Lyftrondata.

Easily auto-extract JSON, XML schemas into relational format

No need to write any complex API, rest services, JSON, and XML parsing jobs. Lyftrondata takes care of all these it converts any data into a relational format and allows you to query it with simple ANSI SQL.​

Emulation compatibility with SQL Server

  • Metadata model exposed by SQL Server, including metadata catalog, system views, stored procedures, and functions
  • SQL dialect supported by SQL Server
  • Tabular Data Stream network protocol as described in Microsoft TDS documentation
  • Data types and conversions, where all data types are normalized automatically into equivalent SQL Server data types

Secure your sensitive data with our encryption functions

Lyftrondata comes with a built-in enterprise data governance framework complying with all of the necessary rules and tools that your team needs to successfully operationalize your program. Amplify your information governance with a robust data lineage model that follows high-quality controls and governance mechanisms.

Perform complex transformations

Skip writing long complex APIs, and transform instantly with SQL. Define data transformations as a standard SQL. Lyftrondata pushes down SQL to data sources and the cloud, making it easy for all users to access the information they need in a timely fashion.

Quickly apply complex joins

Apply high cardinality joins between API sources, S3, Blob and database, without heavily relying on the BI and data engineering teams to set up complex and time-consuming ETLs.

Easily query data from S3, Blob, JSON, Xml like a table

Eliminate traditional ETL/EDW bottlenecks by auto- normalizing API/JSON/XML/S3/Blob/NoSql
sources into ready-to-query relational format. Focus on boosting the productivity of your data professionals and shorten your time to value.

Federate data sources like actual database

Take a leap from data federation technology and focus on performance optimization as well as self-service search and discovery. Spend more time analyzing data than searching for
it.

State-of-the-art facial recognition API

Perform Azure cognitive AI access with our face recognition API function. Be on the top of technology, and use cognitive services that bring AI within reach of every developer—without requiring machine-learning expertise.

Emulation delivers compatibility with the following SQL Server features:

  • Procedural programming constructs: IF, WHILE, DECLARE
  • Temporary tables (stored in memory)
  • Selected SQL session environment variables
  • Security model supported by SQL Server
  • Authentication using Windows Integrated Authentication and SQL Server Standard Authentication (Mixed Mode)
  • Job scheduling model and accompanying stored procedures

Lyftrondata Easy-to-Implement Transformation Functions Supported For

  • Aggregate

  • Analytical

  • Azure Cognitive AI

  • Date & Time

  • Expression

  • Math

  • Metadata

  • Ranking

  • String

  • System

  • Data Parsing

  • Tabular

  • Data Encryption

Let’s get personal: See Lyftrondata on your data in a live Demo

Schedule a free, no-strings-attached demo to discover how Lyftrondata can radically simplify data lake ETL in your organization.

How we do it

Integrate any data source

Connect to supported data source Marketing Cloud and import metadata. Register essential data sets in the catalog and begin real-time analytics.

Query with SQL in real-time

Not all data sources must be replicated to a data warehouse to be used for analytics. Use SQL for any data source and also query data in real-time.

Transform with SQL

Transform or filter the data using SQL that is translated into source data. Combine the data with other data sources.

Use any BI tool

Lyftrondata fully simulates SQL Server on the wire so you can use standard SQL Server drivers available in all BI tools and query Lyftrondata Hub or combine it with other data sources.

Migrate to modern database

Automatically convert data types from the data source to match the target database types. A columnar data pipeline will load the data without delays.

Accelerate BI by prototyping

Shorten BI projects by 4x with a simple trick. First define all required data sets virtually. Build the dashboards on real-time data, consult with business users and replicate the data only when required.

Business benefits of Lyftrondata hub

  • Real-time Analytics

    Query all data sources with simulated Transact-SQL. Get real-time data from data warehouses or source systems during prototyping and data modeling.

  • Smart Data Pre-aggregation

    Accelerate slow queries by materializing their results. Define pre-aggregates with joins, groupings and filtering that are 1000x smaller than original data. Turn any data warehouse into a virtual OLAP cube.

  • Instant In-memory Analytics

    Create a virtual data warehouse without even setting up a target data warehouse. Start with a single node build-in Apache Spark and scale it up to a whole Data Lake after measuring a required cluster size.

  • Global Data Catalog

    Describe all essential data sources and data sets in the data catalog. Use the self-service interface to find the right data.

  • Data Security

    Transparently apply row-access security and dynamic data masking to any data source. Authenticate with Windows Integrated Security (Kerberos) from SQL Server when using any data source.

  • Data Lineage Tracking

    Track down all data sets that will be affected by a change to a table or a column. Find out which source tables and columns are used in any data set, even if it is based on multiple other data sets.

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Supported data sources