Offerings
Sparkflows offers diverse solutions for AI, Generative AI, and data engineering.
With ready-to-use vertical use cases, businesses can implement these technologies quickly and effectively.
Overview
Sparkflows provides a compelling alternative to Alteryx.
Build your workflows with drag and drop using the 500+ nodes. Execute them on your server or on your various compute clusters. Perform data preparation, build machine learning models and powerful analytical apps seamlessly. Easily convert your Alteryx recipes to Sparkflows workflows.
Capabilities
Data Preparation
Sparkflows data preparation capabilities are much more advanced. It has an extensive array of processors, all running distributed and scale to Petabytes of data.
Collaboration
Users can seamlessly work in teams on shared Projects by logging into Sparkflows via their Browser. It also supports Git.
Self-Serve Experience
Sparkflows provides rich Browser based end to end Self-Serve user experience.
Enterprise Data Quality
Sparkflows provides intuitive, easy-to-use, comprehensive Data Quality with a very rich set of Data Quality Rules and Dashboards.
Scalability and pushdown
Sparkflows is completely distributed and runs natively on GCP, Databricks, AWS EMR,HPE, Kubernetes, HDInsights, Apache Spark cluster, Snowflake. It scales to Petabytes of data.
Pricing
Sparkflows is much more competitively priced than Alteryx. Sparkflows has no server license costs. Sparkflows license provides access to all capabilities, any number of ML models etc.
Machine learning and Gen AI
Sparkflows supports H2O, Apache Spark ML, Scikit Learn, Tensorflow, Prophet, ARIMA etc. in its workflows with drag and drop. Sparkflows support 90+ algorithms. Sparkflows supports LLM models from Hugging Face etc.
Analytical Apps
Sparkflows provides extremely rich Analytical Apps experience for Al and Gen Al. The execution of the Apps backend happens on the cluster making it very scalable. It provides low-code UI for Apps.
Governance
Sparkflows provides advanced
governance for access to data, sharing of projects and connections between groups. Sparkflows also provides seamless integration with Git.
Extensiblity
Sparkflows enables users to create new custom Nodes. The custom node can have rich dialog, schema propagation, interactive execution and visualization capabilities.
In-Line Coding
Sparkflows supports SQL, Scala, Python, Jython for inline coding within workflows. Sparkflows also support Code Libraries in Workflows.
Visualization and Dashboard
Sparkflows provides rich Charts, Reports and Dashboards. Reports and
Dashboards are built with drag and drop.
Streaming
Sparkflows supports Stream processing from Kafka, Kinesis etc.
Cloud Integration
Sparkflows provides users rich experience on GCP, Databricks,
AWS,HPE, Kubernetes, Azure HDInsights, Cloudera, Apache Spark clusters etc. It also integrates with GCP Vertex Al and AWS Sagemaker.
Model Serving and ML Ops
Sparkflows enables users to embed models into real-time applications and also score in batch. Sparkflows also integrates natively with systems like MLflow, Sagemaker, Vertex Al. Sparkflows support model comparison, explainability, model details, feature importance etc.
Security and Governance
Sparkflows adopts zero-comprise air-gapped installation and push-down strategy. It offers widest range of User and App Authentication support (Okta, Ping, LDAP, Ranger, Kerbores)
It offers multi-level access control for all types of assets both at global User/Group/Roles and project level. It allows secure sharing of workflows, code security and full-scale Audit-control.
Solutions
Sparkflows provides 100+ templates, 90+ data engineering, Al and Gen Al in-depth solutions out of the box.