What Is Enterprise Data Storage?
Enterprise data storage is a hardware solution that manages large volumes of data for organizations, ensuring that data is securely stored, easily accessible, and efficiently managed. Unlike consumer-grade storage, these systems handle the complexities and scale of enterprise environments, providing higher capacity, performance, and management features. They integrate with various business applications, facilitating data flow and interoperability.
In addition to basic storage functions, enterprise data storage solutions emphasize reliability and data protection. They deploy redundancy measures such as RAID (redundant array of independent disks), snapshotting, and replication to safeguard data against hardware failures and data corruption. These systems also support data deduplication and compression techniques to maximize storage efficiency and reduce costs. As organizations’ data needs grow, these solutions offer scalable options to keep pace with increasing data volumes.
This is part of a series of articles about data lake.
In this article:
- Common Types of Enterprise Data Storage
- Enterprise Data Storage Trends
- Key Considerations When Choosing Enterprise Data Storage Solutions
Common Types of Enterprise Data Storage
1. Direct-Attached Storage (DAS)
Direct-attached storage (DAS) connects directly to a server or workstation without a network interface. This can be via internal drives or external devices connected via USB, eSATA, or other interfaces. DAS offers low latency and high-speed access since the storage is directly attached to the system, making it ideal for applications requiring high performance with minimal network overhead.
However, DAS is limited in scalability and often needs more flexibility for larger enterprise settings. As each DAS unit is directly connected to a specific system, managing multiple DAS devices across an organization can become cumbersome. This limitation makes DAS more suitable for specific use cases, such as small businesses or departments within larger organizations requiring isolated storage.
2. Network-Attached Storage (NAS)
Network-attached storage (NAS) systems are dedicated storage devices connected to a network, providing data access to various clients and devices. NAS units use standard network protocols such as NFS (network file system) or SMB (server message block), making them accessible from different operating systems. One of the significant advantages of NAS is its ease of setup and user-friendly interfaces, making it accessible for users without deep technical knowledge.
NAS systems are for data sharing and collaboration, allowing multiple users and devices to access the same files simultaneously. This makes NAS an excellent option for environments like offices or creative studios where file sharing is essential. Additionally, high-end NAS devices offer features like synchronization with cloud services, automated backups, and media streaming capabilities, enhancing their utility beyond simple file storage.
3. Object Storage
Object storage is a data storage architecture that manages data as discrete units, or “objects,” each consisting of data, metadata, and a unique identifier. Unlike file storage, which organizes data hierarchically, and block storage, which stores data in fixed-size blocks, object storage employs a flat file system, making it limitlessly scalable. This makes it ideal for handling vast amounts of unstructured data like medical records, genomics information, financial documents, multimedia files or backups.
Object storage is highly durable due to its distributed architecture which allows data to be striped across multiple storage devices. Most object storage systems today employ the AWS S3 API, making them compatible with software written for cloud operating systems. This compatibility also makes it ideal for hybrid cloud deployments as a common set of APIs can be deployed on prem and in the cloud, making data mobility seamless.
4. Storage Area Networks (SANs)
Storage area networks (SANs) deliver block-level storage. In this environment, the file system (or database) resides at the server level rather than at the storage level. SANs provide scalability, high performance, low latency and redundancy, making them suitable for mission-critical applications such as databases, ERP systems, and high-transaction environments. These networks use protocols like Fibre Channel or iSCSI (internet small computer systems interface) to facilitate fast data transfers and redundancy features.
SANs support features like snapshotting, cloning, and disaster recovery, though they come with higher complexity and cost. Implementing and managing a SAN requires specialized knowledge and tools, but the benefits of consolidated, high-performance storage often outweigh these challenges for large enterprises.
5. Software-Defined Storage
Software-defined storage (SDS) abstracts storage resources from the underlying hardware using software, providing a flexible and scalable solution. It is usually deployed on industry-standard servers, avoiding the need for proprietary hardware.
SDS describes an architecture rather than a specific protocol, and can be either block, file or object. It decouples storage functions such as management, provisioning, and replication from physical devices, allowing organizations to leverage commodity hardware and reduce costs. This model enables better resource utilization and simplifies storage management across varied environments.
It supports scaling by adding more hardware resources and software instances, making it suitable for rapidly growing data environments. Moreover, SDS provides centralized management and monitoring, offering better visibility and control over an organization’s entire storage infrastructure.
6. Cloud Storage
Cloud storage allows organizations to store data on remote servers accessed via the internet. Public cloud storage providers like AWS, Google Cloud, and Azure offer scalable and flexible storage solutions without the need for managing physical hardware. Cloud storage provides a pay-as-you-go model, making it cost-effective for handling variable storage needs.
5 Expert Tips
Jon Toor, CMO
With over 20 years of storage industry experience in a variety of companies including Xsigo Systems and OnStor, and with an MBA in Mechanical Engineering, Jon Toor is an expert and innovator in the ever growing storage space.
Implement data lifecycle management (DLM) policies: Establish and enforce DLM policies to automate the movement of data through its lifecycle stages, ensuring that inactive or less critical data is moved to cost-effective storage, freeing up high-performance storage for active data.
Leverage hybrid storage solutions: A combination of on-premises and cloud storage can balance cost, performance, and scalability. This hybrid approach allows you to keep sensitive data locally while leveraging the cloud for elasticity and backup.
Regularly audit and optimize storage utilization: Conduct frequent audits to identify underutilized or orphaned storage resources. Optimization tools can help reallocate or reclaim space, ensuring efficient use of storage capacity.
Implement strong data governance frameworks: Establish clear data governance policies to ensure data quality, consistency, and compliance with regulatory requirements. This includes defining roles, responsibilities, and procedures for data management.
Use storage tiering strategically: Classify data based on access frequency and importance, and store it on appropriate tiers. Frequently accessed data can reside on high-performance storage, while infrequently accessed data can be moved to slower, more cost-effective storage.
Enterprise Data Storage Trends
Hyper-Converged and Converged Infrastructure
Hyper-converged infrastructure (HCI) integrates compute, storage, and networking into a single system, simplifying management and deployment. This approach reduces data center complexity, making it easier to manage resources and reduce operational costs. HCI solutions often come with integrated management software, providing a unified view of the entire infrastructure and streamlining administrative tasks.
Converged infrastructure (CI) similarly combines compute, storage, and networking but keeps them as separate components within a managed framework. Both HCI and CI aim to simplify IT operations and improve resource utilization, but HCI offers further integration and ease of use.
NVMe
Non-volatile memory express (NVMe) is a protocol optimized for high-performance SSDs, offering lower latency and higher throughput compared to traditional storage interfaces like SATA and SAS. NVMe is engineered for flash storage, enabling rapid data access and efficient parallelism. This is crucial for workloads requiring fast data processing, such as real-time analytics, AI, and high-frequency trading.
Adoption of NVMe drives is accelerating as organizations seek to leverage its performance benefits. NVMe can significantly reduce data access times, improving overall application performance and user experience.
AI and Analytics Integration
Enterprise data storage systems are increasingly being designed to support AI and data science initiatives within companies. These systems need to handle the high-performance requirements of AI workloads, which involve processing large volumes of data in real time. To enable this, enterprise storage solutions integrate with AI frameworks and tools, providing the necessary throughput and low latency.
Modern storage solutions also offer advanced analytics capabilities directly within the storage infrastructure. These capabilities include built-in data tagging, indexing, and metadata management, which help in organizing and retrieving data more effectively. Additionally, some storage systems come with AI-driven analytics features that can identify patterns, anomalies, and trends within the stored data.
Disaggregated and Composable Storage
Disaggregated storage separates compute and storage resources, allowing each to scale independently. This approach contrasts with traditional, tightly coupled systems where upgrades must be coordinated.
Composable storage takes this a step further by enabling dynamic reconfiguration of storage pools through software. Organizations can allocate storage resources on-the-fly based on workload demands, enhancing agility and responsiveness to changing business requirements. Both disaggregated and composable storage models aim to provide greater flexibility and efficiency in managing enterprise data.
Key Considerations When Choosing Enterprise Data Storage Solutions
1. Capacity
Capacity is a critical factor when selecting enterprise data storage solutions. Organizations must assess their current data needs and future growth to ensure the chosen solution can scale accordingly. Insufficient capacity can lead to disruptions and performance bottlenecks, while excessive capacity can inflate costs without providing additional benefits.
Compression and tiering are features that can enhance capacity management. These features enable efficient storage utilization by compressing files and automatically moving less frequently accessed data to cost-effective storage tiers.
2. Performance
Performance metrics like IOPS (input/output operations per second), throughput (GB/s), and latency are crucial when evaluating storage solutions. Application requirements should be carefully considered as some, such as databases, require high IOPS, while others, such as data streaming, require high aggregate throughput (GB/s). Performance bottlenecks can significantly impact the overall productivity and user experience.
Enterprise storage solutions should support features like SSD caching, tiered storage, and high-speed interconnects to enhance performance. These features optimize data access patterns and reduce latency, ensuring that high-priority workloads receive the required performance levels. Assessment and benchmarking of performance capabilities against actual workloads help in choosing the right solution.
3. Reliability
Reliability is paramount for enterprise data storage, as data loss or downtime can have severe consequences. Storage solutions should offer redundancy, failover mechanisms, and error correction to ensure data integrity and availability. Technologies like RAID, erasure coding, and hardware redundancy help mitigate risks associated with hardware failures and data corruption.
Features such as snapshots, replication, and high availability ensure business continuity and data protection. Regular testing of failover and recovery procedures is essential to verify the effectiveness of these measures. Implementing reliable storage infrastructure minimizes risks and ensures data is consistently available and protected.
4. Security
Security is essential for protecting sensitive data from unauthorized access, breaches, and cyber threats. Enterprise storage solutions should offer security features, including encryption (both at rest and in transit), access controls, and authentication mechanisms.
Data security must be integral to the storage architecture to meet compliance and regulatory requirements. Storage solutions that support relevant security frameworks and integrate with monitoring tools further enhance the overall security posture.
5. Data Recovery
Effective data recovery capabilities are crucial for minimizing downtime and data loss during failures. Enterprise storage architectures should include reliable backup and recovery capabilities, such as snapshots, replication, and automated backup schedules. These ensure that data can be quickly restored to a consistent state following an incident.
Implementing a robust data recovery strategy involves regular testing of backup and restore procedures to verify their effectiveness. Granular recovery options, such as file-level or application-level restores, provide flexibility in addressing different recovery scenarios. Ensuring quick recovery capabilities minimizes operational disruptions and safeguards business continuity.
On-Premise Enterprise Data Storage with Cloudian
Cloudian HyperStore is an on-prem, enterprise data lake that uses a fully distributed architecture to eliminate single points of failure, and enable easily scalability from hundreds of Terabytes to Exabytes. It is cloud native and fully compatible with the Amazon S3 API.
The HyperStore software implementation builds on three or more independent nodes, allowing you to configure a highly-available solution with whatever level of durability is required for your use case. It lets you add as many storage devices as needed, and the additional devices automatically join an elastic storage pool.