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Move to Managed Databases

An AWS Modernization Pathway with TD SYNNEX

The "Move to Managed Databases" pathway focuses on migrating from self-managed databases to fully managed AWS database services. This journey eliminates time-consuming administrative tasks like patching, backups, and scaling, freeing up teams to focus on application development while improving performance, scalability, and reliability.

Triggers & Compelling Events

Excessive Admin Time

DBAs are overwhelmed with patching, backups, and maintenance.

High Licensing Costs

Expensive commercial database licenses are draining the budget.

Performance Bottlenecks

Applications are slow due to database scaling limitations.

Data Gravity Issues

On-premises data hinders cloud application development.

Reliability & DR Concerns

Complex, unreliable backup and failover processes.

Need for Purpose-Built DBs

Relational databases are struggling with modern data types.

1

Awareness & Discovery

Customer experiences pain from self-managed databases and begins to explore managed cloud alternatives.

Partner Actions & Offerings

  • Owner: Partner / TD SYNNEX BDM / AWS PDM
  • Action: Register Deal in AWS Partner Central (ACE)
  • Funding: None at this stage.
  • Services: None at this stage.
2

Opportunity & Qualification

A concrete opportunity is identified. Partner qualifies the lead and builds the initial business case.

Partner Actions & Offerings

  • Owner: Partner / TD SYNNEX SA / AWS SA
  • Action: Qualification call with CoE or local technical pre-sales/SA
  • Funding: OLA funding for applicable opportunities; Windows Server, SQL & Oracle DB
  • Services: None at this stage.
3

Solution Development

The technical solution is designed and validated through workshops and a Proof of Concept (PoC).

Partner Actions & Offerings

4

Customer Proposal

A formal proposal with the target architecture, a phased migration plan, and a clear ROI is presented to the customer.

Partner Actions & Offerings

  • Owner: Partner / TD SYNNEX BDM / AWS MAP aligned account manager
  • Action: Submit Proposal & SOW through TD SYNNEX.
  • Funding: Sandbox Innovation credits.
  • Services: TD SYNNEX SOW & Proposal Support via Services team.
5

Delivery

Execute the database migration, including schema conversion, data replication, and cutover.

Partner Actions & Offerings

6

Support & Optimize

Provide ongoing support, optimize data pipelines and query performance, and help drive user adoption.

Partner Actions & Offerings

Core AWS Services & Training

Key AWS Products

Amazon Aurora, Amazon RDS, Amazon DynamoDB, Amazon DocumentDB, Amazon ElastiCache, Amazon Neptune, Amazon Timestream, Amazon MemoryDB for Redis, Amazon Keyspaces

Enablement & Training

The Modernization Journey: From Pain to Platform

Click the below triggers to see how AWS services solve the customers problem.

Excessive Admin Time

High Licensing Costs

Performance Bottlenecks

Data Gravity Issues

Reliability & DR Concerns

Need for Purpose-Built DBs

From Excessive Admin Time to Automated Operations

By migrating to managed services like Amazon RDS and Amazon Aurora, you offload routine tasks like patching, backups, and high availability to AWS, freeing up DBAs to focus on higher-value activities.

From High Licensing Costs to Cost-Effective Open Source

Moving from commercial databases (e.g., Oracle, SQL Server) to managed open-source compatible databases like Amazon Aurora or Amazon RDS eliminates punitive licensing fees and reduces TCO. Use AWS SCT and AWS DMS to simplify the migration.

From Performance Bottlenecks to Scalable Performance

Amazon Aurora provides commercial-grade performance with the simplicity of open source. For extreme low-latency requirements, Amazon MemoryDB for Redis provides a durable, in-memory option, Amazon ElastiCache offers an in-memory cache, and Amazon DynamoDB delivers single-digit millisecond performance at any scale.

From Data Gravity Issues to Cloud-Native Applications

Migrating on-premises databases to AWS using AWS DMS and AWS SCT moves your data's center of gravity to the cloud, allowing you to build modern, low-latency applications that are co-located with the data.

From Reliability & DR Concerns to Automated Resilience

Managed services like Amazon RDS and Amazon Aurora provide automated backups, point-in-time recovery, and simple multi-AZ deployments for high availability and disaster recovery with just a few clicks.

From Need for Purpose-Built DBs to The Right Tool For The Job

Instead of forcing one database to do everything, use the right tool for the job. Use Amazon DocumentDB for JSON workloads, Amazon Neptune for graph relationships, Amazon Timestream for time-series data, and Amazon Keyspaces for Cassandra workloads to build highly performant, scalable applications.

From Data to Decisions: Powering Databases with AI

Predictive Queries with In-Database ML

Run machine learning predictions directly from your database using familiar SQL commands. Services like Amazon Aurora ML allow you to enrich your data with real-time ML-based predictions for fraud detection, product recommendations, and more, without complex data pipelines.

Powering Generative AI with Vector Search

Build intelligent search and Retrieval-Augmented Generation (RAG) applications. Amazon RDS for PostgreSQL and Amazon Aurora support the `pgvector` extension to store, index, and query ML-generated embeddings, forming the foundation for modern generative AI applications built with Amazon Bedrock.

Automated Performance Insights with AI Ops

Move from reactive to proactive database management. Amazon DevOps Guru for RDS uses machine learning to automatically detect, diagnose, and provide recommendations for a wide variety of database-related performance issues, helping you resolve bottlenecks before they impact customers.

Supporting Documentation