Databricks
Automated deployment of Databricks pipelines
Move from development to production environments faster
& easier with automated deployment of data pipelines to
Databricks clusters.
Data Migration to Databricks
Trying to keep up with increasing data from multiple sources? Facing high reporting and analytics costs? A Data Lakehouse may be the solution—but migrating your current processes into Databricks can come with a myriad of unforeseen technical requirements, learning curves, and risks of project failure.
See how WhereScape can speed up the delivery of a migration.
WhereScape Data Automation with Databricks
95 %
Time Savings
on hand-coding development, refactoring and management tasks.
8x
Developer Productivity
in implementing and managing infrastructure through automation.
6x
Return on Investment
by avoiding failures, filling skill gaps and adding built-in best practices.
Stress-Free Deployments with
Data Lakehouse Automation
WhereScape simplifies data workflow orchestration, scalability, and monitoring in Databricks by automating the deployment and management of data lakehouses.
Near-Limitless Scalability with
Databricks Pipelines Automation
WhereScape automates end-to-end data pipeline development in Databricks for easier data ingestion, transformation, and loading into Databricks clusters.
Benefits of Databricks
Databricks Lakehouse Architecture:
Databricks Lakehouse Architecture blends the best of data lakes and data warehouses to create a unified, high-performance system, providing enterprise-level security, access control, data governance, auditing, retention, lineage, and data discovery tools.
- Transactional Support: Ensures data consistency with ACID transactions, enabling concurrent reads and writes.
- Schema Enforcement and Governance: Supports complex schema architectures like star/snowflake-schemas, with robust governance and auditing mechanisms to maintain data integrity.
- BI Tool Integration: Enables direct use of BI tools on source data, reducing latency and operational costs by eliminating the need for multiple data copies.
- Decoupled Storage and Compute: Facilitates scalability by using separate clusters for storage and compute, accommodating more users and larger datasets.
- Openness: Utilizes open, standardized storage formats (like Parquet) and APIs, allowing diverse tools and engines to access data efficiently.
- Support for Diverse Data Types: Capable of handling structured, semi-structured, and unstructured data, including images, videos, audio, and text.
- Diverse Workload Support: Accommodates various applications, from SQL analytics and real-time monitoring to data science and machine learning.
- End-to-End Streaming: Supports real-time data applications, eliminating the need for separate systems for streaming data.
WhereScape with Databricks:
- Bronze layer: Captures raw data from external sources while maintaining source system structures and vital metadata for historical archiving and auditability.
- Silver layer: Data is cleansed, matched, and merged. This layer supports self-service analytics, ad-hoc reporting, and advanced analytics, prioritizing speed and agility.
- Gold layer: Offers consumption-ready, curated business-level tables optimized for reporting and complex analytics projects.
Additional Databricks Features:
- Unity Catalog: The industry’s only unified and open governance solution for data and AI.
- Built on Apache Spark: Offers high performance for batch and streaming data, analytics capabilities, seamless integration.
- Delta Lake and Apache Iceberg: Open-source table formats, offering reliability to data lakes with ACID transactions and metadata handling.
- Delta Live Tables: Simplifies the construction of reliable data processing pipelines.
- Collaborative Notebooks: Support for multiple programming languages and real-time collaboration.
- Machine Learning Capabilities: MLflow and AutoML for the entire ML lifecycle, from experiment tracking to deployment.
- Generative AI: Optimized for specific tasks, offers deployment solutions, balancing accuracy and efficiency.
- Databricks Assistant: Query data through a conversational, context-aware AI assistant.