Netezza Migration to Databricks on Cloud with Our Automated Migration Product Suite
Existing Challenges with On-Premise Netezza
operational challenges
- On-premises Netezza systems require ongoing maintenance, including hardware upkeep and software updates, which can be resource-intensive.
- Scalability is a complex issue, with significant time and cost associated with expanding or upgrading hardware components.
- Ensuring high availability and minimizing downtime due to hardware failures or system updates is an ongoing operational challenge.
- Meeting security and compliance requirements demands safeguarding physical hardware and ensuring data remains secure within the on-premises environment.
- Implementing effective disaster recovery solutions to protect data is complex and requires a meticulous backup and recovery strategy.
technical challenges
- Managing the complexity of hardware components, such as servers, storage, and networking equipment, demands technical expertise.
- Integrating data from diverse sources and formats into the Netezza system can be technically challenging, necessitating data transformation and ETL processes.
- Fine-tuning the Netezza database for optimal query performance and efficient workload management requires technical expertise and continuous monitoring.
- Applying software updates and patches without disrupting operations can be technically demanding, requiring careful planning and testing.
- Efficiently allocating computing and storage resources to adapt to changing workload demands can be technically complex and requires ongoing adjustments.
business challenges
- The cost of owning and operating on-premises Netezza systems is high, including expenses for hardware, maintenance, and staffing.
- Adapting to evolving business needs and market dynamics can be challenging, as on-premises infrastructure may lack the agility of cloud-based solutions.
- Staying competitive may be challenging when tied to legacy on-premises infrastructure, especially when competitors leverage more agile technologies.
- Finding and retaining skilled personnel with Netezza expertise can be a business challenge, particularly in regions with a limited pool of qualified professionals.
- Assessing the long-term sustainability of on-premises Netezza solutions in a rapidly changing technology landscape is a business challenge, requiring strategic planning for future data needs and technology 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.
- 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
Netezza on-premise data warehouse assessment is done by Eagle – Data Migration Planning Tool using SQL logs and metadata extracted from Netezza. 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 Netezza and Databricks datasets to ensure confidence before the Netezza 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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Oracle to Databricks
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FAQs
What are the benefits of migrating to Databricks?
Some of the key benefits of migrating from Netezza to Databricks are:
- Scalability
- Cost Efficiency
- Data Integration
- Advanced Analytics
- Real-time Processing
- Cloud Compatibility
- Auto-scaling
- Unified Data Platform
- Open Source
How do I migrate Jobs to Databricks?
Migrating jobs to Databricks basically involves three primary stages:
- Legacy System Assessment and Databricks Migration Planning: Datametica’s automated assessment and migration planning tool – Eagle, performs detailed analysis of the legacy on-premise 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 codes – SQLs, UDs, DDLs, 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 systems and Databricks and highlights all the discrepancies in single iteration.
Datametica’s automated data warehouse modernization and cloud migration suite makes migration to Databricks simple, cost effective, and risk free.
