Teradata Migration to Databricks on Cloud with Our Automated Migration Product Suite
Existing Challenges with On-Premise Teradata
operational challenges
- Maintenance and upkeep of on-premises Teradata systems is resource-intensive, involving hardware repairs and software updates.
- Scalability poses challenges, as it’s time-consuming and costly to expand or upgrade hardware components.
- Ensuring high availability and minimizing downtime is an ongoing operational challenge.
- Security and compliance efforts are complex due to the need to protect physical hardware and data within the on-premises environment.
- Implementing effective disaster recovery solutions can be complex and expensive.
technical challenges
- Managing the complexity of hardware components, such as servers, storage, and networking, requires technical expertise.
- Data integration challenges involve transforming and ETL processes for various data sources and formats.
- Performance optimization requires constant fine-tuning, workload management, and query performance monitoring.
- Applying software updates and patches without disrupting operations is technically demanding.
- Efficiently allocating computing and storage resources is technically challenging.
business challenges
- On-premises Teradata systems incur high capital and operational costs, including hardware expenses and maintenance.
- Lack of flexibility and agility can hinder the ability to adapt to changing business needs and market dynamics.
- Tied to legacy infrastructure, businesses might struggle to compete with more agile, cloud-based solutions.
- Talent availability and retention for Teradata expertise can be a challenge, especially in regions with limited qualified professionals.
- Assessing the long-term sustainability and strategic planning for future data needs presents a business challenge in a rapidly evolving technology landscape.
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
- The 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.
- The 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
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 Teradata 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
Teradata on-premise data warehouse assessment is done by Eagle – Data Migration Planning Tool using SQL logs and metadata extracted from Teradata. 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 Teradata and Databricks datasets to ensure confidence before the Teradata 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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Netezza to Databricks
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Hadoop 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 Teradata to Databricks are:
- Scalability
- Cost Efficiency
- Data Integration
- Advanced Analytics
- Real-time Processing
- Cloud Compatibility
- Auto-scaling
- Unified Data Platform
- Open Source
What is Databricks migration?
Migrating your data from the legacy data warehouse (EDW) to Databricks in order to scale your business as per growing business needs and accelerate innovation with capabilities like AI, analytics, etc is known as Databricks migration. Datametica’s automated cloud migration suite – Eagle, Raven, and Pelican – enables a simplified, cost-effective, and risk free migration to Databricks.
