Oracle Migration to Databricks on Cloud with Our Automated Migration Product Suite
Existing Challenges with On-Premise Oracle
operational challenges
- Maintenance and upkeep are resource-intensive, involving hardware and software.
- Scalability complexities entail significant time and cost for expansion.
- Balancing high availability with minimal downtime is an ongoing challenge.
- Meeting security and compliance involves safeguarding physical hardware.
- Implementing effective disaster recovery requires meticulous planning.
technical challenges
- Hardware complexity demands technical expertise.
- Data integration involves various sources and formats.
- Performance optimization necessitates continuous fine-tuning.
- Software updates require careful planning and testing.
- Resource allocation must adapt to changing workloads.
business challenges
- High ownership costs include capital, operational expenses, and staffing.
- Flexibility and agility are hindered by on-premises infrastructure.
- Competitive disadvantages can arise against more agile technologies.
- Talent availability can be limited in some regions.
- Ensuring long-term viability requires strategic planning for future needs and tech trends.
How migrating to Databricks Solves these Challenges
- Databricks leverages cloud infrastructure to provide unlimited infrastructure capacity.
- One tool for complete ETL pipelines, data analytics, instant data visualization, orchestration, and scheduling
- Databricks platform is backed by a very high level of uptime guarantee from the cloud platform.
- Automated and scheduled patch management, upgrades, and fixes without user intervention.
- Complete control over infrastructure and software expenses with detailed cost breakdown, cost forecasting, and ‘pay what you use’ model. No additional cost for data center, power, etc.
- Platform provides capabilities for data governance, lineage tracking, monitoring, and auditing.
- Platform provides capabilities for data governance, lineage tracking, monitoring, and auditing.
- Simpler architecture (databricks) for the implementation of business use cases.
- Easy migration of an existing codebase and integration with a variety of legacy and new technologies.
- Simpler DR implementations are backed by cloud platforms, guaranteeing data availability across regions.
- Capability to immediately scale up and scale down cluster capacity at the job level and project level.
- Simpler integration with other vendor tools is also backed by cloud platform integration capabilities.
- Better security, authorization, and governance controls at the lowest grain of data.
- Databricks enable new clusters, infrastructure, and technologies in minutes for new use case implementation.
- Integrated ML, AI, and analytics capabilities are also available with databricks.
- High cluster uptime is backed by a cloud platform.
- The ability to scale up/down ensures the required processing and storage capacity is always available.
- Simple tools like Jupyter notebooks for ML and AI, instant data visualization, time travel, and many other capabilities can assist business users with a minimal learning curve.
- Address multiple data silos in the course of the databricks migration/modernization program and build governance controls to prevent data duplication.
Our Partnership with Databricks
Datametica’s partnership with Databricks highlights our commitment to delivering excellence to our joint customers. Our collaboration, as a DPP-certified partner, is designed to provide top-tier expertise and support. Here are the key highlights of our partnership:
A strategic alliance at the global level with Databricks allows us to deliver services in all parts of the world
Providing clients with a fully compliant migration product suite that makes migration faster, lower costs and lower risks
Staffed by certified Databricks architects, data engineers and associates
Leveraging Databricks’ unique capabilities in hyper-scale cloud data warehousing, analytics, and machine learning
Enables us to collaborate with Databricks professional services team to successfully deliver large scale migrations
How does Datametica’s Birds seamlessly migrate data to Databricks
eagle
the planner
Architecting an end-to-end migration strategy, with workload discovery, assessment, planning, and cloud optimization.
raven
the transformer
Automated & Optimized code (SQL/Scripts/ETL) conversion to the cloud-native technologies.
pelican
the validator
Automating data validation, reconciliation, and comparison of datasets across two heterogeneous data stores.
How Datametica migrates Netezza to Databricks
- Automated legacy data warehouse assessment and discovery
- Identify workload (metadata, data, and code) dependencies
- Create a detailed plan for migration to Databricks
- Guaranteed 100% automated code conversion to Databricks native and supporting technologies
- Create patterns for target platform
- Auto-generate the pattern for newer migration
- Query Editing for optimized fixes and performance tuning
- Automated data validation and reconciliation
- Data validation at the minutest level (cell-level)
- Data matching between Databricks and on-premise systems
- Once everything is set up, we provide the training and support to keep customers going with the new Databricks data warehous
How to Get Started
Oracle on-premise data warehouse assessment is done by Eagle – Data Migration Planning Tool using SQL logs and metadata extracted from Oracle. This helps in analyzing access patterns, all system activities, and artifacts that are needed to plan the cloud migration strategy.
The process is then taken over by Raven – Automated Workload Conversion Service. It is used to automate and optimize workload (ETL/SQL/Scripts) conversion to Databricks. After the code conversion is done, Pelican – Automated Data Validation Tool, comes into the picture to automate the data validation process between the Oracle and Databricks datasets to ensure confidence before the Oracle system is decommissioned.
This engagement also results in:
Migration Strategy
Migration Plan
Effort Estimation
Solution Architect
Technical Architect
Our Other Solutions
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Hadoop to Databricks
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Teradata to Databricks
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Netezza to Databricks
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FAQs
What are the benefits of migrating to Databricks?
ome of the key benefits of migrating from Oracle to Databricks are:
- Scalability
- Cost Efficiency
- Data Integration
- Advanced Analytics
- Real-time Processing
- Cloud Compatibility
- Auto-scaling
- Unified Data Platform
- Open Source
How to migrate data from Oracle to Databricks?
Migrating from Oracle to Databricks basically involves three primary stages:
- Legacy Oracle System Assessment and Databricks Migration Planning: Datametica’s automated assessment and migration planning tool – Eagle, performs detailed analysis of the legacy on-premise Oracle system, highlighting all the complexities, and creates a detailed, lineage aware cloud migration plan for Databricks migration.
- Code Conversion and Data Migration: On the basis of the plan created by Eagle, Datametica’s automated code transformation service – Raven, translates Oracle codes – SQLs/DS, UDs, ETLs, etc. – into Databricks compatible codes.
- Data Validation: Data validation is an important step as it helps ensure that all the data is successfully migrated and is functional in the new Databricks environment. Datametica’s Pelican is an AI-powered automated data validation tool that performs cell-level validation between legacy Oracle systems and Databricks and highlights all the discrepancies in single iteration.
Datametica’s automated data warehouse modernization and cloud migration suite makes Oracle migration to Databricks simple, cost effective, and risk free.
