Lyftrondata vs Ab-Initio

Challenge The Traditional Method: Overcome the Bottlenecks of ETL/ELT Process

Business critical decisions, future expansion plans, business investment and divestment decisions and everything else require complex reports and massive amounts of data. The required data existed in different silos and was not easily accessible for visualization or analysis. And without a whole lot of preparation and generating real-time reports it was only a dream. The complexities in data management quickly led to the evolution of ETL/ELT systems for generating meaningful insights out of Big Data.
The very core of data management is rapidly evolving because the speed and volume of data is growing faster than current technology can keep up with. Traditional methods utilizing obsolete ETL, ELT and building Legacy data warehouses are far too expensive and is overly complicated that requires more time and effort to build the solutions much less support them! As a result we are seeing many companies missing their SLAs instead of using modern day solutions that don’t have those problems!

What’s Lyftrondata
Lyftrondata is a modern data fabric solution that provides real-time access to any data and enables users to query them with simple ANSI SQL. With Lyftrondata, enterprises can build data pipelines in minutes and shorten the time to insights by 75%, with the power of modern cloud computing of Snowflake and Spark.
Lyftrondata eliminates the time spent by engineers building data pipelines manually and makes data instantly accessible to analysts with simple and standard ANSI SQL. Its prebuilt connectors automatically deliver data to warehouses in normalized, ready-to-query schemas and provide full search on the data catalog.

Why Lyftrondata, a comprehensive  ANSI SQL Platform  is the best

  • Speed

    Fastest response to your queries at a massive scale

  • Density

    Migrates any amount of data from any source of your choice

  • Velocity

    Data transformation possible in a fraction of minutes

  • Simplicity

    Effortless modern data hub for workload migration

  • Time

    Shortest time-to-value and actionable insights

  • Cost

    Huge cost savior for all kinds of migration projects.

Comparative rating index

Not available Available with limited functionalities Available with industry's best functionalities
Highlights Lyftrondata Ab-Initio
Cost
G2 Rating
5 stars 76 reviews
4.3 star 16 reviews
Number of Connectors
300+ connectors
2 connectors
Learning Curve and Time to Build Data Pipeline
1-5 days
15+ days
Team Size
1-10 resources
20-30 resources
Security Protocol
GDPR and HIPPA
None
Deployment
SAAS
On-Premise
PAAS
Core Competencies
Data Pipeline
Automatic ANSI SQL Pipeline. Lyftrondata eliminates the time spent building data pipelines manually and makes data instantly accessible with simple ANSI SQL.
Data Catalog
With Lyftrondata, users can access an enterprise-wide data catalog and data lineage to quickly discover, understand, and manage all their data and keep it up-to-date.
Delta Lake
Lyftrondata arguably shares a better framework to build a sophisticated delta lake on Amazon S3, Blob, and Google Storage.
Data Virtualization
Lyftrondata provides a common abstraction over any data source type, shielding users from its complexity and back-end technologies it operates on. It relies on views that allow users to integrate data on the fly.
Data Replication
Faster and smoother with Lyftrondata, as it quickly replicates all business data to the data warehouse, without the need for maintenance or configuration.
Managed Warehouse
Lyftrondata's large-scale, high-performance, and cost-effective warehouse is designed to collect the data from more than 150 sources, transform it with familiar SQL, and analyze it in BI tools for instant insights, all with zero coding absolutely.
Data Sharing
With Lyftrondata's robust and secured sharing framework, 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.
API Data Models
Lyftrondata empowers users to avoid creating time-consuming code and use SQL to query any data, both structured and semi-structured.
Data Preparation
Data preparation with Lyftrondata enables cleaning, structuring, and enriching raw data into the desired output for analysis. This functions to clean and transform data from one or more sources to improve its quality prior to its use in business data analysis.
SQL Workbench
Use SQL to query any data, both structured and semi-structured. Our Warehouse supports automatic zero code JSON/XML/API parsing to relational format. Analyze instantly with ANSI.
Data Governance
Lyftrondata comes with a built-in enterprise data governance framework complying with all of the necessary rules and a robust data lineage model that follows high-quality controls and governance mechanisms.
Highlights Lyftrondata Ab-Initio
Cost
G2 Rating
4 stars 13 reviews
4.3 star 21 reviews
Number of Connectors
300+ connectors
2 connectors
Learning Curve and Time to Build Data Pipeline
1-5 days
15+ days
Team Size
1-10 resources
20-30 resources
Security Protocol
GDPR and HIPPA
None
Deployment
SAAS
On-Premise
PAAS
Core Competencies
Data Pipeline
Automatic ANSI SQL Pipeline. Lyftrondata eliminates the time spent building data pipelines manually and makes data instantly accessible with simple ANSI SQL.
Data Catalog
With Lyftrondata, users can access an enterprise-wide data catalog and data lineage to quickly discover, understand, and manage all their data and keep it up-to-date.
Delta Lake
Lyftrondata arguably shares a better framework to build a sophisticated delta lake on Amazon S3, Blob, and Google Storage.
Data Virtualization
Lyftrondata provides a common abstraction over any data source type, shielding users from its complexity and back-end technologies it operates on. It relies on views that allow users to integrate data on the fly.
Data Replication
Faster and smoother with Lyftrondata, as it quickly replicates all business data to the data warehouse, without the need for maintenance or configuration.
Managed Warehouse
Lyftrondata's large-scale, high-performance, and cost-effective warehouse is designed to collect the data from more than 150 sources, transform it with familiar SQL, and analyze it in BI tools for instant insights, all with zero coding absolutely.
Data Sharing
With Lyftrondata's robust and secured sharing framework, 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.
API Data Models
Lyftrondata empowers users to avoid creating time-consuming code and use SQL to query any data, both structured and semi-structured.
Data Preparation
Data preparation with Lyftrondata enables cleaning, structuring, and enriching raw data into the desired output for analysis. This functions to clean and transform data from one or more sources to improve its quality prior to its use in business data analysis.
SQL Workbench
Use SQL to query any data, both structured and semi-structured. Our Warehouse supports automatic zero code JSON/XML/API parsing to relational format. Analyze instantly with ANSI.
Data Governance
Lyftrondata comes with a built-in enterprise data governance framework complying with all of the necessary rules and a robust data lineage model that follows high-quality controls and governance mechanisms.

HighlightsLyftrondataAb-Initio
Ease of Use

Easy to use click-based user interface delivers a codeless development environment.
Access Rights

With Lyftrondata, users can easily manage access rights and roles on various levels of granularity.
User Management

Lyftrondata uses users and roles for access management. Permissions can be assigned on a per-user or per-role basis.
Role Management

Lyftrondata comes with several predefined roles which define the actual permissions for the given users.
Auto Data Type Conversion

Automated data type mapping keeps detecting and loading incremental data to the target.
Scheduler

Lyftrondata supports a user-defined recurrent task called a job which is used along with a scheduler.
Tagging

Universal data catalog tag-based search of Lyftrondata enables users to have full control of their data catalog and do the search with ease.
Workflow

Lyftrondata makes the data available in minutes and automates data workflows using SQL, thereby cutting down the development, cost, time, and efforts by 80%.
Execution History

With Lyftrondata, users can get a list of recently executed statements under the execution history.
Broken Pipeline Alerts

Get alerts and notifications on broken pipelines.
Row Level Security

Lyftrondata's modern architecture provides row-level access security to the users and makes it easy to share data without writing any single piece of code.
Column Level Security

Lyftrondata's modern architecture provides column-level access security to the users and makes it easy to share data without writing any single piece of code.
Notification and Alerts

Lyftrondata comes with a build-in notification system to alert users when the source is changed.
User Activity History

Lyftrondata uses the industry-leading log-based change data capture technology to continuously detect and load incremental changes with minimal impact on the source systems.

HighlightsLyftrondataAb-Initio
API Normalization

Lyftrondata connectors automatically normalize the data from API, JSON, and XML formats.
SQL Support

Use SQL to query any data, both structured and semi-structured.
Data Hub

With Lyftrondata's data virtualization capabilities, link cross-platform sources easily and quickly, without moving the data.
Support, Documentation and Training

Get the round-the-clock training & support with Lyftrondata.
Transformation

Have your staff trained in the new tools and architecture of Lyftrondata which enables the swift transition to your team.
Real-time Integration

All transformations are defined in standard SQL, which are pushed down to the data warehouse in their native SQL for better performance. Use default templates for common transformations like Star Schema and integration techniques, eliminating time spent on tedious tasks.
Built-in Spark Parallel Processing

Continuously load your real-time data to destination with minimal impact on source systems. Get instant insights in BI tools with the latest data sets.
Data Profiling

The robust architecture of Lyftrondata allows parallel processing of 2000+ data warehouse queries.
Auto Data Masking

Lyftrondata empowers enterprises to do data masking and encryption at the field level. Users can control the security thoroughly.
Proactive Monitoring

Monitors data quality and send alerts based on changes made in data sources.

HighlightsLyftrondataAb-Initio
Ease of Admininstration
Ease of Building Pipeline Automatically
Ease of Writing SQL to Query API
Quality of Support
Ease of Setup and Configuration

Highlights Lyftrondata Ab-Initio
Ease of Use
Easy to use click-based user interface delivers a codeless development environment.
Access Rights
With Lyftrondata, users can easily manage access rights and roles on various levels of granularity.
User Management
Lyftrondata uses users and roles for access management. Permissions can be assigned on a per-user or per-role basis.
Role Management
Lyftrondata comes with several predefined roles which define the actual permissions for the given users.
Auto Data Type Conversion
Automated data type mapping keeps detecting and loading incremental data to the target.
Scheduler
Lyftrondata supports a user-defined recurrent task called a job which is used along with a scheduler.
Tagging
Universal data catalog tag-based search of Lyftrondata enables users to have full control of their data catalog and do the search with ease.
Workflow
Lyftrondata makes the data available in minutes and automates data workflows using SQL, thereby cutting down the development, cost, time, and efforts by 80%.
Execution History
With Lyftrondata, users can get a list of recently executed statements under the execution history.
Broken Pipeline Alerts
Get alerts and notifications on broken pipelines.
Row Level Security
Lyftrondata's modern architecture provides row-level access security to the users and makes it easy to share data without writing any single piece of code.
Column Level Security
Lyftrondata's modern architecture provides column-level access security to the users and makes it easy to share data without writing any single piece of code.
Notification and Alerts
Lyftrondata comes with a build-in notification system to alert users when the source is changed.
User Activity History
Lyftrondata uses the industry-leading log-based change data capture technology to continuously detect and load incremental changes with minimal impact on the source systems.

Highlights Lyftrondata Ab-Initio
API Normalization
Lyftrondata connectors automatically normalize the data from API, JSON, and XML formats.
SQL Support
Use SQL to query any data, both structured and semi-structured.
Data Hub
With Lyftrondata's data virtualization capabilities, link cross-platform sources easily and quickly, without moving the data.
Support, Documentation and Training
Get the round-the-clock training & support with Lyftrondata.
Transformation
Have your staff trained in the new tools and architecture of Lyftrondata which enables the swift transition to your team.
Real-time Integration
All transformations are defined in standard SQL, which are pushed down to the data warehouse in their native SQL for better performance. Use default templates for common transformations like Star Schema and integration techniques, eliminating time spent on tedious tasks.
Built-in Spark Parallel Processing
Continuously load your real-time data to destination with minimal impact on source systems. Get instant insights in BI tools with the latest data sets.
Data Profiling
The robust architecture of Lyftrondata allows parallel processing of 2000+ data warehouse queries.
Auto Data Masking
Lyftrondata empowers enterprises to do data masking and encryption at the field level. Users can control the security thoroughly.
Proactive Monitoring
Monitors data quality and send alerts based on changes made in data sources.

HighlightsLyftrondataAb-Initio
Ease of Administration
Ease of Building Pipeline Automatically
Ease of Writing SQL to Query API
Quality of Support
Ease of Setup and Configuration

Lyftrondata's value propositions that set it apart from traditional data pipeline tools for modern data warehouse, modernization & migration

  • Data explosion

    With every passing minute, enterprises are saving petabytes of data in the form of emails, messages, tweets, call logs, IoT and much more. The nature of data from all these sources is highly unstructured and requires powerful tools for consolidation and analysis. Legacy systems fail to combine data from all these sources for a holistic view of business and for more data-driven decision making.

  • Real time data for decision support

    With the evolution in business processes, enterprises require solutions that are highly flexible and offer them solutions for real-time decision support. The data scenario started changing within seconds and minutes and traditional systems failed to offer the agility required by the modern enterprise.

  • Cost effective solutions

    Storage and maintenance costs turned out to be major concern with legacy systems, however with the advent of cloud data warehouse services like Amazon RedShift and Snowflake these rising costs are no longer a concern. The modern cloud data warehouse services are highly scalable in nature and can automatically scale up or down based on the surge in the data. They also offer pay as you go services and charge based on usage.

  • Access to all data points

    One of the biggest advantages of modern data pipelines is to gain access to all your data points and gain a holistic view of your business. Modern data pipelines help you to bring all your data together without any technical limitations making analysis simple for all stakeholders.

  • Agile, modern data fabric solution

    With the rapid changes in the complexity and volume of data, enterprises quickly decided to adopt more scalable and resilient systems that allowed them to leverage the full potential of their data and as a result the modern data pipe lines came into existence.
    Modern data pipelines are processing elements that move data from one system to another, at times transforming the data along the way. They are highly scalable, distributed, decoupled and allow us to interact with real-time data.
    The data is ingested directly without any cleaning introducing a lot of noise in the target data warehouse. To avoid such pitfalls, data pipelines organize data to make analysis and reporting lot easier.
    Data pipelines include a set of processes and technologies that automate the transformation, management, visualization and consolidation of data from multiple resources to derive valuable business insights.

START PLANNING YOUR MODERNIZATION

Want more information about how to solve your biggest data warehousing challenges? Visit our resource center to explore all our informative and educational ebooks, case studies, white papers, videos, and much more.

Lyftrondata Resources

Lyftrondata vs Talend

Download the report and compare the benefits of Lyftrondata against the top ETL/ELT tool - Talend.

Lyftrondata vs Informatica

Download the report and compare the benefits of Lyftrondata against the top ETL/ELT tool - Informatica.

Lyftrondata vs Matillion

Download the report and compare the benefits of Lyftrondata against the top ETL/ELT tool - Matillion.

Scroll to Top