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Competitive Advantage

Why customers choose Sparkflows
over Competitors?

Self-Service ISVs

No Native Data Lake Integration | 

Not Completely Distributed | Less Scalable

Proprietary Algorithms | Weak Open Integrations | 

Not Extensible | Vendor Lock-Ins

Very Expensive

Comprehensive Native Data Lake Integration | Completely Push Down | Much better Distributed Processing | Higher Scalability

Open Technologies | Strong Integrations | End-2-End Self-Service | Fully Extensible | No Vendor Lock-Ins

Competitively Priced

Sparkflows Vs Competitors – Diving into details

Data Lake Integrations

Open Technologies

Machine Learning

Analytical Apps and Reports

Low-Code & Extensibility

Data Quality

Vertical Solutions

Automations

Title
Sparkflows
Competitor
Details

Integration with Data Lakes on cloud or on premise

Support for Open Technologies like Apache Spark, H2O, Airflow, Prophet, ARIMA, MLflow etc.

Support for various ML engines and ML algorithms in workflows

Support for building and executing Analytical Apps and Reports

Ability to code within the workflows, ability to generate open-source code and extend the feature set.

Ability to code within the workflows, ability to generate open-source code and extend the feature set.

Out of the box vertical solutions and ability to build powerful end to end new solutions

Automations like auto data profiling, auto-ml, automated editor etc.

Sparkflows Vs Competitors – Diving into details

There are 100K+ Data Lake Instances and growing. They are on all the clouds and on premise. They hold data from all kinds of sources and are hence the best places to perform Machine Learning. However, they are also complex to operate and to write distributed code. Security and scalability are key pieces of the Data Lakes.

Data Lake Integrations
Data Browsers for HIVE, Glue Catalog, Snowflake etc.
Deep Integration with Data Lakes
Distributed Processing
Title
Sparkflows
Nearest Competitor

This Competitor only supports Snowflake well

This Competitor  does not have much support for Data Browsers

 This Competitor  has light security integrations

This Competitor  is not inherently built to run distributed on the Data Lakes

Sparkflows integrates with AWS EMR, Glue, Databricks, Azure HD Insights, Google Data Proc, Cloudera, Kubernetes, Snowflake. Best support for Open Data Lakes

Sparkflows provides Data Browsers for all of them

Sparkflows has deep security integrations with AWS IAM Roles, Kubernetes, provides Impersonation

In Sparkflows all the workflows and algorithms run distributed

Open Technologies

All Enterprises have a number of Technologies deployed. These include MLflow, Airflow, etc. Its much easier to them to have the Self-Serve system work on these open technologies rather than bring in new technologies.

Airflow
MLflow
AWS Deequ, Great Expectations for Data Quality
All types of Security / SSO / Authn libraries
Title
Sparkflows
Nearest Competitor

This Competitor does not integrate with Airflow

This Competitor does not integrate with MLflow

This Competitor does not integrate with them

No other competitor has such wider support for security libraries

Sparkflows integrates deploy with Airflow

Sparkflows integrates with MLflow

Sparkflows integrates with AWS Deequ and Great Expectations

Sparkflows has detailed support for all types of Security libraries (Apache Ranger, kerbores, PingId, Okta, IAM Roles etc.) with extremely strong Governance and Auditing

Catalog 

Competitors lack in such extensive support of catalogs

Sparkflows supports connectivity with Data Hub, Unity Catalogs and external Data lineage using API

Machine Learning

There are certain machine learning engines which all the Enterprises use. These include Scikit-learn, Apache Spark ML, H2O, Prophet, ARIMA, Keras, Tensorflow. Enterprises expect the self-serve technologies to deploy support them.

Scikit-learn
H2O
Prophet
Keras / Tensorflow
Title
Sparkflows
Nearest Competitor

This Competitor partially supports Scikit-learn

This Competitor does not support H2O in workflows

This Competitor does not support Prophet in workflows

This Competitor does not support deep learning technologies in workflows

Sparkflows supports Scikit-learn

Sparkflows supports H2O

Sparkflows supports Prophet

Sparkflows supports Deep learning technologies

AutoML

This Competitor supports AutoML

Sparkflows supports AutoML

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