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Data Security: The Advantages of Hybrid vs. Public Clouds

As an industry, we often discuss proper and effective data analysis, however data security is actually even more important. After all, what good is effective analysis without securing the foundational data? Additionally, in 2024 there are numerous clouds one can persist data within including public, private, and hybrid cloud environments. This raises the natural question of how to properly secure your data for the cloud.

Public, Multi-Cloud, and Hybrid Clouds

It helps to start with a baseline of common terminology used throughout the industry. Public clouds are publicly accessible compute and storage services provided by third-party cloud providers. Multi-cloud is simply an architecture composed of services originating from more than one public cloud.

A hybrid cloud is composed of different interconnected public and private clouds that work together sharing data and processing tasks. Interconnectivity between hybrid environments is established with local area networks, wide area networks, VPNs, and APIs. Like all cloud environments, hybrid environments leverage virtualization, containerization, and software-defined networking and storage technologies. And dedicated management planes allow users to allocate resources and scale on-demand.

Security Benefits of Hybrid Cloud Architecture

A hybrid cloud is ideal when you want to leverage both the scale of public cloud services while also securing and retaining a subset of your data on-premises. This helps an organization retain and secure compliance and to address data security policies. Sensitive datasets can be retained on-premises while less sensitive assets may be published to public cloud services.

Hybrid clouds provide the ability to scale on-demand public services during peak workloads. Organizations reap cost optimization by being able to leverage both on-premises and public cloud services and storage assets. And there are disaster recovery and geographic failover benefits to hybrid cloud solutions. Finally, a hybrid cloud enables businesses to gradually migrate legacy applications and datasets from on-premises to public cloud environments.

Actian’s Cloud Data Platform

The Actian Data Platform coupled with DataConnect provides no-code, low-code and pro-code data integrations that enable hybrid cloud data solutions. Actian DataConnect provides enterprise-grade integration with connectivity support for both our public and private cloud data platforms. Public cloud data services can be provisioned using SOAP or REST API access with configurable authentication. Users are able to schedule and execute data integration jobs that securely move data across all Actian Data Platform environments. Both at-rest and in-flight data encryption can also be implemented.

The Actian Data Platform’s data warehousing component can be scaled up and down in real-time, this helps greatly with right-sizing workload scale. The Actian public cloud data warehouse is built on decades of patented real-time query processing and optimizer innovations. In summary, the Actian Data Platform is unique in its ability to collect, manage, and analyze data in real-time, leveraging its native data integration, data quality, and data warehouse capabilities in an easy-to-use single platform.

The post Data Security: The Advantages of Hybrid vs. Public Clouds appeared first on Actian.


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Author: Actian Corporation

What Trends to Expect in 2024 in Enterprise Storage? (Part One)


Looking ahead to the new year, we’ve identified seven trends in enterprise storage for 2024. In part one, we’ll define and explore the first four trends. The remaining three trends will be the focus of part two. This information will help equip you to prioritize and be successful in the new year.  Trend: Freeing up […]

The post What Trends to Expect in 2024 in Enterprise Storage? (Part One) appeared first on DATAVERSITY.


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Author: Eric Herzog

Data Management for a Hybrid World: Platform Components and Scalability

For most companies, a mixture of both on-premises and cloud environments called hybrid cloud is becoming the norm. This is the second blog in a two-part series describing data management strategies that businesses and IT need to be successful in their new hybrid cloud world. The previous post covered hybrid cloud data management, data residency, and compliance.  

Platform Components 

There are essential components for enabling hybrid cloud data analytics. First, you need data integration that can access data from all data sources. Your data integration tool needs a high degree of data quality management and transformation to convert raw data into a validated and usable format. Second, you should have the ability to orchestrate pipelines to coordinate and manage integration processes in a systematic and automated way. Third, you need a consistent data fabric layer that can be deployed across all environments and clouds to guarantee interoperability, consistency, and performance. The data fabric layer must have the ability to ingest different types of data as well. Last, you’ll need to transform data into formats and orchestrate pipelines. 

Scaling Hybrid Cloud Investments 

There are several costs to consider for hybrid cloud such as licensing, hardware, administration, and staff skill sets. Software as a Service (SaaS) and public cloud services tend to be subscription-based consumption models that are an Operational Expense (Opex). While on-premises and private cloud deployments are generally software licensing agreements that are a Capital Expenditure (Capex), subscription software models are great for starting small, but the costs can increase quickly. Alternatively, the upfront cost for traditional software is larger but your costs are generally fixed, pending growth. 

Beyond software and licensing costs, scalability is a factor. Cloud services and SaaS offerings provide on-demand scale. Whereas on-premises deployments and products can also scale to a certain point, but eventually may require additional hardware (scale-up) and additional nodes (scale-out). Additionally, these deployments often need costly over-provisioning to meet peak demand.  

For proprietary and high-risk data assets, leveraging on-premises deployments tends to be a consistent choice for obvious reasons. You have full control of managing the environment. It is worth noting that your technical staff needs to have strong security skills to protect on-premises data assets. On-premises environments rarely need infinite scale and sensitive data assets have minimal year-over-year growth. For low and medium-risk data assets, leveraging public cloud environments is quite common including multi-cloud topologies. Typically, these data assets are more varied in nature and larger in volume which makes them ideal for the cloud. You can leverage public cloud services and SaaS offerings to process, store, and query these assets. Utilizing multi-cloud strategies can provide additional benefits for higher SLA environments and disaster recovery use cases. 

Hybrid Data Management Made Easy 

The Actian Data Platform is a hybrid and multi-cloud data platform for today’s modern data management requirements. The Actian platform provides a universal data fabric for all modern computing environments. Data engineers leverage a low-code and no-code set of data integration tools to process and transform data across environments. The data platform provides a modern and highly efficient data warehouse service that scales on-demand or manually using a scheduler. Data engineers and administrators can configure idle sleep and shutdown procedures as well. This feature is critical as it greatly reduces cloud data management costs and resource consumption.  

The Actian platform supports popular third-party data integration tools leveraging standard ODBC and JDBC connectivity. Data scientists and analysts are empowered to use popular third-party data science and business intelligence tool sets with standard connectivity options. It also contains best-in-class security features to support and assist with regulatory compliance. In addition to that, the data platform’s key security features include management and data plane network isolation, industry-grade encryption, including at-rest and in-flight, IP allow lists, and modern access controls. Customers can easily customize Actian Data Platform deployments based on their unique security requirements. 

The Actian Data Platform components are fully managed services when run in public cloud environments and self-managed when deployed on-premises, giving you the best of both worlds. Additionally, we are bringing to market a transactional database as a service component to provide additional value across the data management spectrum for our valued customers. The result is a highly scalable and consumable, consistent data fabric for modern hybrid cloud analytics. 

The post Data Management for a Hybrid World: Platform Components and Scalability appeared first on Actian.


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Author: Derek Comingore

How to Maximize Multi-Cloud Data Governance
The transition from hybrid to multi-cloud environments is more than just a buzzword: It’s a fundamental shift in how organizations manage and utilize their data. As these complex architectures evolve, the importance of robust multi-cloud data governance cannot be overstated. This article aims to provide an in-depth analysis, tips, and best practices for maximizing data […]


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Author: Ben Herzberg

How to Build a Growth-Focused Data Analytics Tech Stack in 2023

In 2023, building a growth-focused data analytics tech stack is all about cloud deployment flexibility and cloud-native support. According to Gartner, more than 85% of organizations will embrace a cloud-first principle by 2025, but they will not be able to fully execute their digital strategies unless they use cloud-native architectures and technologies. Cloud-native technologies empower organizations to build and run scalable data analytics in modern, dynamic environments such as public, private, and hybrid clouds.

Cloud Deployment Models

Your data analytics solution should support multi-cloud and hybrid cloud deployment models for greater flexibility, efficiency, and data protection. Here’s a brief overview of each model and its benefits:

Multi-cloud simply means that a business is using several different public clouds such as AWS, Microsoft Azure, and Google Cloud, instead of just one. Why multi-cloud? Below are some of the compelling reasons:

  • Being able to choose the best-fit technology for a cloud project.
  • Getting the best value by choosing providers with the lowest cost and having leverage during price negotiations.
  • Obtaining different geographic choices for cloud data center locations.

A hybrid cloud model uses a combination of public clouds, on-premises computing, and private clouds in your data center with orchestration among these platforms.  Hybrid cloud deployment is useful for companies who can’t or do not want to make the shift to cloud-only architectures. For example, companies in highly regulated industries such as finance and healthcare may want to store sensitive data on-premises, but still leverage elastic clouds for their advanced analytics. Other businesses may have applications that would require too much expensive movement of data to and from the cloud, making on-premises a more attractive option.

Cloud-Native Technologies

Beware; even though most analytics databases today run in the cloud, there are huge and significant differences between cloud-ready and cloud-native. Let’s explore what cloud-native means and its benefits.

The Cloud Native Computing Foundation defines cloud native as:

“Cloud native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach.”

“These techniques enable loosely coupled systems that are resilient, manageable, and observable. Combined with robust automation, they allow engineers to make high-impact changes frequently and predictably with minimal toil.”

Below are some of the key benefits of a cloud-native analytics database versus a cloud-ready analytics database.

  • Scalability: On-demand elastic scaling offers near-limitless scaling of computing, storage, and other resources.
  • Resiliency: A cloud-native approach makes it possible for the cloud-native database to survive a system failure without losing data.
  • Accessibility: Cloud-native uses distributed database technology to make the database easily accessible.
  • Avoid Vendor Lock-In: Standards-based cloud-native services support portability across clouds.
  • Business agility:  Small-footprint cloud-native applications are easier to develop, deploy, and iterate.
  • Automation: Cloud-native databases support DevOps processes to enable automation and collaboration.
  • Reduced cost. A cloud native database allows you to pay-as-you-go and pay for only resources that you need.

Get Started with the Actian Data Platform

The Actian Data Platform provides data integration, data management, and data analytics services in a trusted and flexible platform. The Actian platform makes it easy to support multi-cloud and hybrid-cloud deployment and is designed to offer customers the full benefits of cloud-native technologies. It can quickly shrink or grow CPU capacity, memory, and storage resources as workload demands change. As user load increases, containerized servers are provisioned to match demand. Storage is provisioned independently from compute resources to support compute or storage-centric analytic workloads. Integration services can be scaled in line with the number of data sources and data volumes.

Start your free trial of the Actian Data Platform today!

The post How to Build a Growth-Focused Data Analytics Tech Stack in 2023 appeared first on Actian.


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Author: Teresa Wingfield