Lyftrondata Revenue and Competitors

Location

N/A

Total Funding

SaaS

Industry

Estimated Revenue & Valuation

  • Lyftrondata's estimated annual revenue is currently $14.2M per year.(i)
  • Lyftrondata's estimated revenue per employee is $160,000

Employee Data

  • Lyftrondata has 89 Employees.(i)
  • Lyftrondata grew their employee count by -12% last year.

Lyftrondata's People

NameTitleEmail/Phone
1
CEO & Co-FounderReveal Email/Phone
2
Chief Technology Officer & Co FounderReveal Email/Phone
3
Sales EngineerReveal Email/Phone
4
Sales EngineerReveal Email/Phone
5
Graphic Designer & Video EditorReveal Email/Phone
6
Software EngineerReveal Email/Phone
7
Software EngineerReveal Email/Phone
Competitor NameRevenueNumber of EmployeesEmployee GrowthTotal FundingValuation
#1
$3.9M320%N/AN/A
#2
$1.5M1838%N/AN/A
#3
$1M10-17%N/AN/A
#4
$19.7M12319%N/AN/A
#5
$14.2M89-12%N/AN/A
#6
$2.2M2723%N/AN/A
#7
$1.1M11-15%N/AN/A
#8
$15.7M9844%N/AN/A
#9
$10.1M7013%N/AN/A
#10
$6M4727%N/AN/A
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What Is Lyftrondata?

Lyftrondata eliminates the time spent by engineers building data pipelines manually and makes data instantly available for insights. Lyftrondata Key Differentiators: > Create a Data Pipeline in Minutes: Register over 100+ types of data sources in one place. Choose the most valuable data sources and replicate them to the cloud. > Power Modern Delta Lake & Data Warehouse: Lyftrondata enables you to build a modern data warehouse and data lake in just a few clicks. Normalize all data sets and load the data to the data warehouse. Apply complex transformations with SQL when needed. > Shortens Time-to-insights: Empower data-savvy users to find and prepare the data they need for analytics. Enable real-time access to any data source from any BI tool. > Unlimited Compute: Lyftrondata enables you to compute on Databricks Spark and Snowflake. Thus, you have the flexibility to choose to compute on either of these modern platforms. > Integrate Multiple Clouds: Build a single view of data across different clouds and regions. Replicate data between different regions of the clouds and put them in sync. > Phase Transition to the Cloud: Migrate on-premise data warehouses to the cloud step-by-step. Create data pipelines for migrated data warehouses and legacy data warehouses in real-time. Not all data warehouses may be moved to the cloud in one step. > Build an Agile Data Culture: Empower data users to find and prepare the data they need in analytics. A fast data strategy based on a combination of a modern data pipeline and real-time data saves delays in data preparation. > Ensure Data Governance in the Cloud: Build a searchable data catalog of valuable data sources. Apply table, row, and column security to any data source on-premise, SaaS, or in the cloud. Build a governed data lake integrated with the enterprise active directory for authentication.

keywords:N/A

N/A

Total Funding

89

Number of Employees

$14.2M

Revenue (est)

-12%

Employee Growth %

N/A

Valuation

N/A

Accelerator

Company NameRevenueNumber of EmployeesEmployee GrowthTotal Funding
#1
$12.9M8911%N/A
#2
$300M891%$4.2B
#3
$12.9M89-4%N/A
#4
$35M8913%N/A
#5
$12.9M8935%N/A