Data Stage Vs Lyftrondata

Legacy ETL, ELT Methods
Things of Past!

The very core of data management is rapidly evolving and traditional ETL /ELT methods are not being able to support fast changing business needs along with the high on volume data. So are these methods things of the past already? Mostly.YES!

Obsolete ETL, ELT are overly complex, difficult to maintain, and costly to extend. As a result, enterprises spend more time, efforts and cost managing their data and at last, end up missing their SLA’s.

To handle such shortcomings, enterprises are opting modern data platforms that are highly flexible and agile in nature.

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What’s DataStage

A high-performance parallel framework, available on-premises or in the cloud.DataDtage helps to extended metadata management and enterprise connectivity and Integration of heterogeneous data, including big data at rest (Hadoop-based) or big data in motion (stream-based), on both distributed and mainframe platforms

What’s Lyftrondata

Lyftrondata is a modern data platform that provides real-time access to any data and enable users to query them with simple ANSI SQL. With Lyftrondata, enterprises can build data pipeline in minutes and shorten the time to insights by 75% with the power of modern cloud compute of Snowflake and Spark.

The modern data platform eliminates the time spent by engineers building data pipelines manually, and makes data instantly accessible by providing real-time access with simple ANSI SQL. Lyftrondata prebuilt connectors automatically deliver data to warehouses in normalized, ready-to query schemas and provide full search on data catalog.

Why Lyftrondata

Highlights Old Way Lyftrondata Way
Processing of Data Pipeline
Repeated and Complex
Simple, Fast and Secured
Highly time-consuming
Modifications in Data Pipelines
Unplanned and Troublesome
Fully Automated and Speedy
Lots of efforts required to learn and perform the tedious process
Team Size
Big Team of Experts
Few Resources
Negligible learning time and Minimal efforts
Minimal efforts
Timeframe to build Data Pipelines
2+ Months
Few Clicks in A Couple of Days

Lyftrondata vs DataStage

Key Differentiators DataStage Lyftrondata
Unlimited cloud scalability
Modern cloud architecture
Unlimited cloud concurrency
Robust cloud security
Data hub support
Field level access control
Pipeline execution plan
One click database clone
ELT support
ANSI SQL database simulation
Colmnar data pipeline
Analyze data with ANSI Sql
Cube support
Semantic layer rotating tables
Data replication
Auto encryption
Data governance
Data dictionary
Logical data warehousing support
Universal data model for agile BI
Universal data catalog tag based search
Auto datatype conversion
Automatic data lineage
Dynamic data pipeline
Automatic data pipeline
Auto Json, Xml, API conversion to normalized structure
Source layer data model
Cluster caching
Native Spark & Hadoop clusters integration (like Databricks, EMR, Hd Insights, Hortonworks, Google Hadoop)
Native BI tools integration (Like Looker, Tabelau, Power BI, Microstrategy, Domo, SAP BO, Sisense, Thoughtspot)
Native ML tools Integration (Like Alteryx, R, Jupyter Notebook)
Native Snowflake bulk loading & streaming
One click migration to Snowflake
Self service data pipeline
Source change notification
Full ANSI Sql database query support

Why Lyftrondata

We will enable your business to make data-driven decisions by:
  • Empowering

    Your business with cost-effective, scalable data solutions.

  • Enabling

    Now 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 relational format and allow you to query it with simple ANSI sql.

  • Eliminating

    Manual data pipeline complexity so you can access your data easily.

  • Shorten

    Shorten time to insights and cut data management process by 75%.

  • Pre built connectors

    Automatically deliver data to warehouses in normalized schemas.

  • Modern governed data lake

    Lyftrondata enables data governance with data catalog, data model, data definition, data lineage, tagging and enterprise data dictionary search.

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 usable 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 to 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 Data Stage Vs Lyftrondata or combine it with other data sources.

Migrate to modern database

Automatically convert data types from 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.

Our Modern Data Ecosystem