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Posts by David Berliner:

Silk's Impact on Customers’ Cloud Cost Efficiency

Silk's Impact on Customers’ Cloud Cost Efficiency

Revolutionizing Cost Efficiency in the Cloud

In the challenging economic landscape of 2025, organizations are under immense pressure to rationalize spending and optimize costs. Even as software budgets are expected to increase and cloud adoption continues to rise, the demand for transparent cost savings and financial justification in purchasing has become paramount. Silk stands at the forefront of this transformation, empowering enterprises to free significant cloud spend for new innovation and growth while enhancing performance and operational efficiency.

Get More for Less with Cloud Database as a Service

Get More for Less with Cloud Database as a Service

In the evolving landscape of cloud computing, businesses are constantly seeking ways to optimize their database management strategies. Organizations can tightly optimize their workloads on cloud infrastructure as a service (IaaS), but that requires significant upfront planning and ongoing oversight. For those that want to offload more of the responsibilities, two prominent options are Cloud Database as a Service (Cloud DBaaS) solutions that include human database administrators (DBAs) as a managed service, and cloud-based Platform as a Service (PaaS) solutions that rely on purely automated processes. This blog post aims to examine the cost efficiency benefits of Cloud DBaaS with managed DBA services compared to automated PaaS solutions. 

Cloud PaaS vs Cloud DBaaS: What is the Best Managed Database Solution for SQL Server?

Cloud PaaS vs Cloud DBaaS: What is the Best Managed Database Solution for SQL Server?

As businesses continue to migrate their workloads to the cloud, selecting the right managed database solution becomes crucial. Microsoft SQL Server, a backbone for many organizations, requires careful consideration when choosing between different cloud offerings. In this post, we’ll compare managed SQL Server solutions available on Silk, Microsoft Azure, Amazon Web Services (AWS), and Google Cloud, focusing on their architectural workload requirements, database engine capabilities, resiliency, operational models, and innovation ecosystems.

6 Key Considerations for Adopting Cloud Database as a Service

6 Key Considerations for Adopting Cloud Database as a Service

As organizations increasingly look to the cloud for their database workloads, it’s essential to carefully plan and align your strategy with your business objectives. Based on extensive experience working with customers, we’ve identified six critical topics that many organizations need to explore when moving their databases to the cloud: 

Cloud Snapshots: Use Cases, Challenges, and How to Use Them Effectively

Cloud Snapshots: Use Cases, Challenges, and How to Use Them Effectively

In today’s information-driven world, we operate at the speed of data. The success of many great businesses is due to how quickly they and their teams can gain insights and use them to make effective business decisions. From healthcare to retail, FinTech to manufacturing, organizations that empower their top talent and key systems with rapid access to data see outsized benefits.  

4 Challenges Organizations Face with Database Management in the Cloud

4 Challenges Organizations Face with Database Management in the Cloud

In the ever-evolving technology landscape, organizations are grappling with many challenges in managing their database environments. Over the past year, our team completed a comprehensive exploration of these challenges and revealed four common experiences that stand out prominently. This blog post aims to dissect these challenges and shed light on the critical issues faced by organizations. Along the way, we’ll share how the new Silk Cloud Database as a Service (DBaaS) offering helps organizations overcome these database management challenges.

How SimCorp Turned its Software into SaaS and You Can Too!

How SimCorp Turned its Software into SaaS and You Can Too!

In the rapidly evolving landscape of cloud computing, companies face critical decisions regarding their SaaS architecture. Navigating these challenges successfully requires strategic thinking, innovation, and a proactive approach. I recently sat down with Ulrik Elstrup Hansen, VP and Head of SaaS Innovation at SimCorp to hear their intriguing cloud journey story. SimCorp is a prominent player in the investment management industry that recently transformed its platform into a cutting-edge Software as a Service (SaaS) offering. In this blog post, I’ll delve I’ll share insights from Ulrik into SimCorp’s cloud journey and the key decisions that paved the way for their SaaS success.

Latest Updates to the Silk Data Virtualization Platform

Latest Updates to the Silk Data Virtualization Platform

At Silk, we pride ourselves on our ability to deliver fast performance, improved manageability, increased resiliency, and greater cost efficiency for customers’ business-critical applications. Which is why we are always striving to take our platform to the next level: we want lightning-fast performance, the smoothest manageability, the strongest resiliency, and cost-efficiency that will have you diving into a pile of money from your cost-savings like you’re Scrooge McDuck.

Pushing the Limits of the Cloud

Pushing the Limits of the Cloud

We feel very proud and fortunate at Silk for the quality of organizations that choose to work with us, both as customers and business partners. We get to help world-class companies migrate and optimize business-critical workloads in the cloud. When you work with one of the top 10 retailers in the world to not just “survive” black Friday but to optimize it, you learn a lot about what organizations are demanding from the cloud.  

An Onramp to an Optimized Cloud

An Onramp to an Optimized Cloud

Years ago, when it came to data platforms, there was a pretty consistent and direct correlation between the size of a company (in employees or revenue) and the size of its data resources. It was rare to find a smaller organization with large-scale data challenges.