Enterprise workloads place significant demands on the storage environment. How your data is managed significantly influences the success of your data project. Ultimately, the project cost, performance, and uptime all rely on choosing the most suitable storage solution for their specific needs. Furthermore, your project’s long-term success depends on the flexibility to accommodate growth and architectural evolution.
Just as workloads vary widely, so do the capabilities of various data management platforms. To make the optimal choice, it’s important to evaluate your current and future needs, and understand how various platforms can meet them.
The Cloudian Secure Hybrid Data Lake offers a unique combination of capabilities that make it ideal for capacity-intensive workloads that require cloud-like capabilities, but in an on-premises setting.
Why a Data Lake Is Essential
Let’s start with the fundamental question of the need for a data lake. The Cloudian HyperStore Data Lake is a centrally managed, distributed repository that allows for the storage of unstructured data at any scale.
It supports multiple data types from various sources and types, including object data for modern applications and file data for legacy applications.
The data lake is differentiated from traditional storage in several ways:
- Scalability: Offers limitless scale and non-disruptive modular growth to accommodate both current requirements and future expansion.
- Multi-tenancy: Allows the data lake to be securely shared by multiple workloads, each with its own set of access controls and a distinct namespace. There is no need to deploy multiple storage systems to accommodate various workloads.
The Cloudian Data Lake is self-protecting to ensure exceptional data availability. Erasure coding delivers multiple levels of data and device redundancy. And, the system can be configured for disaster recovery with built-in replication features that maintain data copies across sites under your policy-based management.
By providing a cloud-like storage environment, the Cloudian Data Lake enables complex analytical queries and operational reporting across diverse datasets, accommodating a myriad of use cases from big data analytics to machine learning.
A Key Difference Maker: Bi-modal Support
An additional feature that differentiates the Cloudian Data Lake is bi-modal data access. This means that both file and object-based apps can access both file and object data types. Thus, data is universally accessible across both legacy and modern apps.
This is especially useful in data analysis applications where the data, which could be a collection of images or video content, is stored in a file format while the analysis software was written for the cloud and therefore uses the S3 API for data access. In this case, the data may be stored in the Cloudian Data Lake, in its original format, and accessed directly by a modern app. This eliminates the need for middleware or data transformation in data access.
Security at the Forefront
Naturally, security is critical in any storage environment that will house sensitive data. And Cloudian delivers a multi-level security approach to meet this need, including access controls, data encryption for data at rest and in flight, secure shell for intrusion defense, and data immutability for ransomware protection.
Cloudian backs this up with a robust set of security certifications. HyperStore’s FIPS 140-2 Level 1 validation by NIST, plus compliance with SEC Rule 17a-4(f), CFTC, FINRA, and others, bolsters Cloudian’s commitment to rigorous data protection. Meeting NIST 800-88 data sanitization standards underlines Cloudian’s commitment to maintaining data integrity and security.
The Hybrid Advantage
In this context, “hybrid” refers to the seamless integration of public cloud services with on-premises data centers. This duality is strategic for organizations looking to leverage the scalability and flexibility of the cloud while retaining the control and performance of local storage systems. In this future-proof architecture, you can leverage the benefits of on-premises management—data sovereignty, low latency, and cost—while maintaining full capability to interchangeably employ the cloud where that is the preferred solution. Hybrid means data and application portability, which in turn gives you flexibility.
Cloudian offers multiple options for hybrid integration, including with AWS Hybrid Edge products, including AWS Outposts, and AWS Local Zones. Only Cloudian is offered by AWS as local, S3-compatible storage for those solutions.
Cloudian’s best-in-class native S3 API ensures full data fidelity and application compatibility, while the data tiering integration with AWS, Azure, and GCP provides seamless management across both on-premises and cloud platforms.
AI Workloads: Ready and Optimized
Artificial Intelligence (AI) workloads demand high performance, scalable storage that can manage vast datasets. Cloudian’s architecture is engineered to support AI initiatives seamlessly by integrating with popular machine learning libraries such as PyTorch and TensorFlow.
These integrations provide GPU connectivity and provide simple, direct access to vast datastores in the Cloudian Data Lake, thus enabling efficient data processing and model training workflows.
Conclusion
Cloudian’s Secure Hybrid Data Lake provides assured data security and compliance in a hybrid architecture that embraces the flexibility of the cloud while sustaining the autonomy of on-premises solutions. It addresses the needs of AI and machine learning applications, providing a future-proof platform to accommodate your data management needs today and into the future. With a Cloudian Data Lake, you are empowered to harness the full potential of your data.
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