The unified EDB Postgres® AI intelligent platform brings an unparalleled approach to addressing challenges associated with managing transactional, analytical, and AI workloads across hybrid and multi-cloud environments. EDB Postgres AI solves the challenges involved in migrating from legacy data infrastructures to an open source database approach that fosters innovation and integration with modern cloud-native stacks.
As part of our platform, the EDB Postgres AI Cloud Service enables organizations to deploy fully managed EDB Postgres on Amazon Web Services (AWS), Microsoft Azure, or Google Cloud—all long-standing partners of ours. In the case of AWS, the company offers their own native Postgres-compatible managed services—Amazon RDS and Amazon Aurora. In our just-published White Paper, “EDB Postgres AI: How to Reduce Your TCO and Improve Postgres Performance on AWS”, we provide a guide for technology leaders who want to examine the various Postgres offerings with the AWS ecosystem and see how they compare to the EDB Postgres® AI Cloud Service.
This blog highlights the informative Postgres database-as-service analysis detailed in the White Paper, including how you can manage cloud infrastructure costs, enhance database performance, and avoid cloud lock-in with the EDB Postgres AI Cloud Service on AWS.
Comparing AWS platform-native Postgres solutions
When compared to self-managing PostgreSQL databases, RDS and Aurora offer streamlined setup, automated maintenance and high availability, reduced administrative overhead, and enhanced reliability. Aurora and RDS can help you manage and run cloud databases without worrying about the underlying infrastructure, but they each have different features that set them apart.
- RDS provides a flexible and scalable solution for setting up and operating a relational database and supports MySQL, PostgreSQL, Oracle, Db2, SQL Server, and MariaDB. RDS simplifies routine database tasks by automating provisioning, backups, basic patch management, and handling routine administration.
- On the other hand, Aurora is a proprietary database engine built by AWS that offers compatibility with MySQL and PostgreSQL, while offering high performance, scalability, and reliability. Aurora achieves higher performance through a proprietary storage architecture that enhances resilience and performance across availability zones and regions.
- Specific business needs can help drive your decision-making between these two options. Aurora may be the better choice for performance, scalability, and high availability, despite the higher cost. Meanwhile, RDS offers a broader range of database engine options and may be more cost-effective for specific applications that don’t require the absolute highest performance.
EDB Postgres AI + AWS: Better Together
Our strategic alliance with AWS enhances the EDB Postgres AI platform capabilities, multi-cloud data infrastructure solution, and product roadmap.
As a result, the EDB Postgres AI Cloud Service closes the high availability gap for Postgres running on AWS, offering up to 99.995% availability by using active/active, geo-distributed architectures needed to assure business continuity. You can migrate to Postgres more easily than ever by using the Oracle Compatibility Mode and suite of integrated EDB migration tools and services.
For enterprise databases supporting globally distributed workloads, regional cloud outages and disruptions in AWS can significantly deteriorate user experience and disrupt business operations. Beyond downtime, database latency is especially problematic for SaaS and customer-facing applications running in multi-cloud environments. Additionally, for a globally distributed user base, the data in Postgres cloud services must adhere to regional differences and policies, as well as comply with data governance regulations. EDB Postgres AI Cloud Service addresses these collective business and customer demands with EDB Postgres Distributed, providing continuous high availability Postgres operations on AWS, with up to 99.995% guaranteed uptime.
In comparison, even with every replication enabled, RDS only offers a 99.95% uptime service level agreement (SLA), and Aurora provides a 99.99% SLA.
Ease Deployment and Reduce TCO with EDB Postgres AI Cloud Service on AWS
In addition to performance and security, deployment ease and total cost of ownership (TCO) are top-of-mind concerns for enterprises scrutinizing Postgres cloud database options.
When compared to Amazon RDS and Aurora I/O-Optimized, EDB Postgres AI offers superior deployment flexibility, performance, and reduced TCO when deployed on the customer’s AWS cloud infrastructure (“bring your own account”). When running in an organization’s AWS cloud infrastructure, EDB Postgres AI Cloud Service provides a lower-cost, higher performance Postgres solution—offering greater resilience, security, and control—than RDS, Aurora Standard, and Aurora I/O-vOptimized.
Additionally, you can access AWS Marketplace pricing for EDB Postgres AI Cloud Service solutions, while reducing your AWS spend commitments.
As a result, you benefit from reduced TCO, quicker time to market, and enhanced innovation capabilities, with EDB handling deployment, monitoring, high availability, replication, backups, and encryption with EDB Postgres AI Cloud Service.
Learn more—download the White Paper to get a side-by-side analysis of how the EDB Postgres AI Cloud Service on AWS compares to Amazon RDS and Aurora I/O-Optimized.
You can get started today with your fully managed EDB Postgres AI Cloud Service experience with $300 in AWS cloud credits.
It’s a financial estimate that incorporates all costs linked to buying, deploying, using, and retiring a product or service.
Imagine you are acquiring a new computer system. The TCO includes the purchase price of the hardware, expenses such as installation, software licensing, initial training of employees, maintenance fees, costs for software updates, additional training sessions as software evolves, and potential downtime during repairs and upgrades.
A basic calculation for TCO is the sum of the initial cost, maintenance cost, and potential remaining costs of the asset, minus the asset’s salvage value.
- Define the scope and objectives of the asset. Understand its intended use, ownership duration, and any specific performance requirements.
- Identify costs and their categories. A basic categorization can be acquisition, operating, or personnel costs.
- Gather data and quantify costs. Forecast maintenance needs, calculate expected energy consumption, and assess planned upgrades.
- Calculate the present TCO by finding the sum of the asset’s initial cost, maintenance cost, and potential remaining costs minus the asset’s salvage value.
- Analyze and interpret the TCO data, make informed decisions, and implement cost-control strategies.
Both are financial metrics but serve different purposes. TCO focuses on the combined costs of owning and operating an asset from start to finish, while ROI focuses on the returns made relative to the initial investment in that asset.
It’s a comprehensive financial assessment that helps organizations make more informed financial decisions. By calculating TCO, they can better understand the long-term effects and value of their investments, manage their budgets wisely, negotiate better terms with vendors, and better prepare for and anticipate potential financial burdens.
This is a contractual agreement between vendor and buyer that details the comprehensive costs linked to an asset. Such agreements provide transparency and facilitate informed decision-making, leading to more strategic vendor-buyer relationships.
PostgreSQL cloud databases offer advanced security and compliance features expected of a modern cloud service, including:
- Data encryption
- All data is encrypted in transit and at rest, using TLS 1.2 or higher for network traffic and AES-256 for data at rest, protecting sensitive information from unauthorized access.
- Access controls
- Granular access control is implemented using SSO and RBAC policies, managing user access, and permissions to enhance security.
- Compliance
- Many providers ensure compliance with critical standards and regulations like SOC2 Type I and II, PCI, and GDPR, which is crucial for organizations with specific regulatory requirements.
- Network isolation
- Network isolation provides an additional layer of protection from unauthorized access, critical in preventing potential cyberattacks.
- High availability and disaster recovery
- Many services offer up to 99.99% availability in disaster recovery scenarios as part of their SLA, ensuring databases remain operational and minimizing downtime and data loss.
- Monitoring and support
- 24/7 monitoring and support are standard, ensuring prompt identification and resolution of security issues, essential for maintaining database integrity and security.
It is a PostgreSQL relational database run in a cloud environment that provides benefits similar to cloud computing, including increased speed, improved scalability, greater agility, and reduced costs.
The cloud model for hosting PostgreSQL databases depends on your organization's needs and goals. The advantages of each of the five models are:
- Private cloud (on-premise or remote)
Private clouds allow organizations to fully customize their infrastructure to meet performance, security, or regulatory needs. They provide enhanced security since resources are kept private, crucial for handling sensitive data or strict compliance. Costs are also more predictable, usually fixed based on capacity rather than variable usage, which helps with budgeting and planning. - Public cloud
Public clouds offer scalability, allowing PostgreSQL databases to scale up or down based on demand quickly. They're cost-effective for variable workloads with a pay-as-you-go model and provide access to a broad ecosystem of integrated services and innovative tools to enhance database functionality. - Hybrid cloud
Hybrid clouds combine the advantages of private and public clouds, keeping sensitive data on-premises while leveraging public cloud scalability for non-sensitive applications. This mitigates single points of failure, ensures higher availability, and helps meet regulatory requirements. - Multi-cloud
Using multiple clouds can prevent vendor lock-in, allowing organizations to choose the best services and pricing from different providers. This approach optimizes operations, reduces downtime risks, and enhances business resilience by not relying on a single cloud provider. - Polycloud
Polycloud lets organizations use specialized services from different providers when their unique capabilities are best for specific PostgreSQL management tasks. This harnesses each provider's strengths for efficiency, performance, and a competitive edge. For instance, one cloud could gather and process IoT data while another handles complex analytics.
Maximize PostgreSQL Performance with EDB’s Expertise
Explore how EDB optimizes PostgreSQL performance on AWS and lowers TCO
More Blogs
