Build delta lake on S3, Blob, Google Storage and get continuous intelligence

Adopt a sophisticated way for building your delta lake on S3, Blob and Google Storage, and optimize for cost and performance while running big data analytics, artificial intelligence (AI) and machine learning (ML). Automatically sync your data inside delta Lake where you further transform it with SQL.

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Overview What you Get How it Works Process Architecture Benefits FAQ Other Products Modern Ecosystem

Process

FAQ

Modern Data Ecosystem

Build high performing delta lake on S3, Blob and Google Storage

Lyftrondata empowers data-driven enterprises build delta lake on the Amazon S3 ecosystem and save thousands of engineering hours and significantly reduce the total cost of ownership. The platform handles all the infrastructure development, empowering users to skip engineering work and go straight to analysis with their favourite BI tool.

Avoid writing lengthy codes, use simple SQL to query any data. Lyftrondata architecture supports automatic zero code JSON/XML/API parsing to relational format and allows users to analyze instantly with ANSI.

Reduce the risk and experience a secured distribution of actionable intelligence. Lyftrondata not only helps you to stay in control of your data, but also empowers business analysts and consumers with modern, AI-powered, self-service analytics capabilities.

Amazon S3

Blob

Google Storage

Apache Spark

Eliminate the complexity with Lyftrondata's simplicity

Velocity

0 +

Parallel Query on S3

Speed

0 %

Faster Results to Insights

Cost

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Reduction in cost

Time

0 X

Faster Delta Lake Development

Density

0 X

Faster Business Decisions

Simplicity

0 X

Faster Learning

What you get

Query with familiar ANSI SQL

Avoid writing lengthy codes, use simple SQL to query any data. Lyftrondata architecture supports automatic zero code JSON/XML/API parsing to relational format and allows users to analyze instantly with ANSI.
Simplify data ingestion on S3

Ensure secured streaming of data from varied sources on S3, ensuring your delta lake is always optimized and irrigated with the most recent data sets.
Data storage on S3 for lifelong

Forget all the traditional storage hassles, and think only about storing your data, both raw or Parquet/ORC files, on S3 and make it consumption-ready by applying industry best practices.
Quickly apply complex joins

Apply high cardinality joins between S3 and database without heavily relying on the BI and data engineering teams to set up complex and time-consuming ETLs.
Faster query performance

Load the data in S3 without any delays and without worrying about structure or schema. Data is loaded from the data source, data transformations are applied on the fly as SQL expressions and the transformed data is streamed directly to the warehouse.
Unlimited cloud compute

Lyftrondata’s columnar architecture automatically scale to support any amount of data, workloads and applications without requiring data movement, data marts or data copies.

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How it works

Lyftrondata delta lake acts as an anti-corruption layer, allows nested tagging by resource groups, and ensures effective and efficient use of data. Lyftrondata accepts an S3 delta lake as yet another data source that is registered in Lyftrondata. The validated tables from the delta lake are tagged in Lyftrondata which is the portal to the delta lake. All additional views of the source data are defined as views. New data sources are evaluated in Lyftrondata first before being loaded to the S3 delta lake.

Get started in minutes, not months with these agile steps. Zero code & zero setup required.

Ingest Your Data on S3 in a fraction of minutes

Simply ingest all your data on S3 and be up and moving in minutes. Without any help from developers, Lyftrondata enables you to choose your most valuable data and pulls it from all your connected data sources in just one click.

Business Analyst

I feel more aligned with the agile process as now I can analyze any data without worrying about any technical know how.

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Empower your analytics with out of the box relational data model

Once the data is ingested, you could easily normalize it from any non relational format to relational format. Lyftrondata connectors automatically convert any source data into normalized structure of ANSI Sql and push down the data pipeline processing as an ELT to the native cloud data warehouse.

Data Analyst

I have a better control on the data analysis process as now I can run rapid fast queries against the API’s which I never thought possible.

Built for the agile data culture for your data

Next, query your data from S3, blob and Google Storage directly with Lyftrondata. Analyze massive volumes of this real-time data in visualization tools and get instant answers to your store performance. Over 100 integrations empower you to use your favorite tools to map data, build and visualize custom reports and more.

Data Architect

I am able to do the architecture and requirement gathering by simply writing ANSI Sql queries for the API sources which use to be the taboos for me.

Analyze your data from any BI/ML tools

Transform or filter the data using SQL that is pushed down to target. Enable a true Extract-Load- Transform to avoid extra data copies.

ETL Developer

I am able to build my data pipeline in few clicks and load billions of records to my warehouse and also able to do cross platform joins on the API sources with ease.

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Analyze your data from any BI/ML tools

Visualize and explore your data metrics in beautifully designed dashboards or any BI tool such as Tableau, Looker, Google Data Studio, Excel, Google spreadsheet. Get insights across products, channels, customers, and more.

BI Analyst

I have a better response from the BI reports and able to connect with API/Json/XML based sources in just fewer clicks.

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Data sharing is data caring

Define, categorize and find all data sets in one place. Share these data sets with other experts with zero code and drive better insights and user experience. This data sharing ability is perfect for companies who want to store their data once, share it with other experts and use it multiple times, now and in the future. We build the best data sharing process around your data stack. So say goodbye to the complex API, FTP and Email manual data sharing processes and simple on board your consumers to the Lyftrondata platform in just few minutes mins.

Our Agile Team

We are in full control of our data exchange process and easily able to share the data instantly and collaborate with teams with ease without worrying about writing complex API, FTP, Email for data sharing.

The secret salt of Lyftrondata's delta lake

Ingest

There is nothing easier than connecting your data from different sources to one source and avoid complicated tasks of preparing data and setting up complex ETL processes. This layer ensures a hassle-free process of connecting with source connectors like S3, Blob, Salesforce, Marketo, Shopify, Oracle, and more.
Delta Lake

The layer of Lyftrondata automates labor-intensive data engineering work. Users could effortlessly build data pipelines in a fraction of minutes by using a visual interface and SQL.
Storage

This layer is responsible for storing the data securely and effectively. It delivers the most updated data sets and empowers users to combine it with their existing data for the deepest insights.
Compute

This functions for optimized process and better load performance with push down on inbuilt Spark, AWS EMRand Azure HD Insights. It is meant to process voluminous data effectively and efficiently at lightning speed.
Metadata

Under the covers of the compute layer, Lyftrondata possesses metadata that works to improve the overall performance capacity. This layer takes care of scheduler, alerts, workflow, data catalog, logs, monitoring, execution plan, and more.
Security

Considered as the heart of Lyftrondata, this layer handles one of the most crucial functions of enforcing security and encrypts key management. This functions for encryption, tagging, masking, access rights, and role management.
Visualize

This innermost layer allows analyzing, visualize and explore the massive volume of data from disparate data sources, empowering users to drive real-time insights for business decisions.

Business benefits of Lyftrondata's delta lake

Ensure Data Accuracy

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.

Advanced Collaboration

Rapid changes to data sets are always welcome and easy to manage in Lyftrondata. Designed for full content reuse and sharing, Lyftrondata allows for easy propagation of changes that take place among different users and systems.

Self-service data sharing

This allows different users to access data from different regions in a data hub. With Lyftrondata’s robust and secure data sharing you can enable governance on your data hub and easily maintain one to one, one to many and many to many relationships with your customers & partners.

Data protection

The governance framework of Lyftrondata validates and enhances the quality of data and is designed to protect the data from misuse. These capabilities ensure data is up to date, accessible, and eventually removed at appropriate points in its lifecycle.

Data accessibility and rights

With a centralized data governance model, control who can access what data. Secure your data to prevent users from seeing forbidden information. Lyftrondata gives analysts all the data discovery functionality they want, and IT administrators the governance they need.

FAQ

Why should I choose Lyftrondata Governed Delta Lake?

Lyftrondata empowers data-driven enterprises build delta lake on the Amazon S3, Blob and Google Storage and save thousands of engineering hours and significantly reduce the total cost of ownership. The platform handles all the infrastructure development, empowering users to skip engineering work and go straight to analysis with their favourite BI tool.

How is data sharing handled in its framework?

Lyftrondata modern architecture provides row and column level access security to the users so, it makes it easy to share data without writing any single piece of code. A data set could be shared internally, between different operating groups and could also be easily transported to the external commodities, eliminating the use to implement a sharing tool.

Does it help in data collaboration?

How does Lyftron promise secure access to my software data like user data, passwords, accounts, and more?

Lyftrondata enables enterprise-level security with a built-in security model and support for standard security frameworks and protocols. Its embedded security system allows data masking, field-level restrictions and architecture that automatically scales up and down.

Control the security and access of your data securely at the column and row level. Lyftrondata enables robust security for data sharing by enabling access control at the pipeline, database, table, column, schema level.

What would be the cost?

Please write to us at [email protected] for details related to pricing.

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