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.

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Eliminate the complexity with Lyftrondata's simplicity

Velocity 2000+

Data Warehouse Parallel Queries

Speed
75%

Faster Results To Insights

Cost
60%

Reduction In Cost

Time
200X

Faster Implementation

Density
100X

Faster
Migration

Simplicity
1500X

Faster
Learning

Lyftrondata pipes professional architecture

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.

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.

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.

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.

Lyftrondata easy-to-implement transformation functions supported for

Aggregate

Analytical

Azure Cognitive AI

Date & Time

Expression

Math

Metadata

Ranking

String

System

Data Parsing

Tabular

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.

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.

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.

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.

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.