Data storage is an important part of computing and information technology. As organizations and individuals generate more data every day, finding ways to store it efficiently and cost-effectively is a priority. What is the most common method for storing data today? There are a few major options to consider.
Local Storage
One of the most basic forms of data storage is local storage on a computer or device. This includes the internal hard drive on a desktop or laptop computer, the solid state drive on a smartphone or tablet, or even external USB flash drives. Local storage has the advantage of allowing fast access speeds since the data is stored on the device itself. However, there are capacity limits and the data is tied specifically to that device. If the device is damaged, stolen, or lost, the data may be difficult to recover. Local storage works well for personal computers and mobile devices, but is not practical for large-scale enterprise storage needs.
Hard Disk Drives
For many years, the hard disk drive (HDD) has been the default local storage component in computers. HDDs store data on quickly rotating magnetic platters. They have traditionally offered more storage capacity for lower cost compared to solid state drives. However, HDDs are mechanical devices making them more prone to failure over time, especially with shocks or vibration. HDDs also have slower read/write speeds compared to solid state options.
Solid State Drives
Solid state drives (SSD) store data on microchips rather than magnetic platters. With no moving parts, they are more durable and shock-resistant. SSDs also offer much faster read/write speeds, making them popular in high performance devices and situations where responsiveness is critical. However, SSDs have historically had lower storage capacity and higher prices per gigabyte compared to HDDs. The price gap is narrowing as SSD technology continues to improve.
Removable Media
Another category of local storage is removable media. These are storage devices designed to be portable and easily transported between different computers and devices. Examples include:
– Optical discs like CDs, DVDs, and Blu-ray discs
– USB flash drives, SD cards, and other external solid state devices
– Tape drives designed for backup and archiving
Removable media offers an easy way to take data on the go or share between devices and locations. Capacities for optical discs and flash drives now range from a few gigabytes up to multiple terabytes. However, removable media can be small and easy to damage or lose. It is not as durable or secure as other storage options.
Network Attached Storage
For storing large amounts of data securely within an organization, network attached storage (NAS) is a common choice. NAS devices contain multiple hard drives and connect directly to a local area network. This allows organizations to centralize data storage and backups for many users and computers to access.
NAS devices are available as commercial off-the-shelf products with capacities from a few terabytes up to petabytes of data. They can be configured with features like data redundancy, backup, and access controls. NAS provides easily scalable storage that can grow as an organization’s needs expand. Multiple users can access files simultaneously for collaboration. The downside is that NAS can have high upfront costs and requires technical expertise to manage and maintain.
Storage Area Networks
Taking network storage to the next level is the storage area network (SAN). SANs are enterprise-scale centralized storage systems that connect servers and users over a high-speed fiber network dedicated to storage traffic. This provides very fast access speeds to large storage volumes. SANs commonly use RAID technology to replicate and distribute data across multiple hard drives for redundancy and failover protection. Storage capacity in a SAN can scale to exabytes.
SANs require significant technical expertise to set up and manage the specialized networking equipment involved. They are found in large companies that need immense storage capacity and lightning fast access speeds to serve hundreds or thousands of users. The hardware and maintenance costs make SANs prohibitively expensive for smaller businesses.
Cloud Storage
One of the biggest data storage trends in recent years is cloud storage. With cloud storage, data is stored on remote servers accessed over the internet. Providers like Amazon, Google, Microsoft, Dropbox, and Box offer plans for both individual consumers and business organizations.
The benefits of cloud storage include:
– Access your data from anywhere with an internet connection.
– No need to worry about managing local storage hardware.
– Scales easily to accommodate growth.
– Often lower costs compared to traditional storage infrastructure.
– Data redundancy and backup included.
Of course, storing data remotely also comes with privacy and security concerns for some. But major cloud providers offer robust security protections to help mitigate this. Even with the risks, cloud storage adoption continues to accelerate thanks to the convenience and flexibility it provides users.
Cloud Storage Options
There are a few main categories of cloud storage to choose from:
– **Public cloud** – Shared storage resources provided by third-party cloud providers. Multiple customers use the same infrastructure.
– **Private cloud** – Customized storage infrastructure dedicated to a single organization. Fully managed by that organization.
– **Hybrid cloud** – Mix of both public and private cloud resources. Sensitive data kept private while non-critical data goes to the public cloud.
The type of cloud model utilized depends on an organization’s specific workload requirements, budget, and security needs.
Database Storage
A discussion of data storage is not complete without mentioning databases. A database stores structured information in tables with rows and columns that can be queried and filtered to derive insights. Relational databases like Oracle, MySQL, and Microsoft SQL Server power most enterprise applications and analytics today.
Database storage occurs primarily on HDDs, SSDs, SAN or NAS devices. Cloud-based database services like Amazon RDS or Azure SQL Database also growing increasingly popular. Database performance depends heavily on having an optimized storage infrastructure with sufficient IOPS (input/output operations per second) to support complex queries under load. As data volumes explode, high-performance storage becomes critical.
Some key developments in database storage include:
– **In-memory databases** – Store entire dataset in RAM for blazing fast throughput. Enables real-time analytics on huge data.
– **Object storage** – Store unstructured data of any type like images, videos, etc. alongside structured database data.
– **Columnar databases** – Store data by column rather than row to optimize for analytics. Improves compression and scan speeds.
So in addition to scaling up traditional storage, optimizing database technology itself is an important consideration.
Data Warehouse Storage
Related to databases, dedicated data warehouses are often required for business analytics and reporting. Used for storing huge volumes of historical data coming from transactional systems and other sources, data warehouses enable complex analytical queries across massive datasets.
To support data warehouses, high performance and scalable storage is absolutely critical. Latency or slow queries will significantly limit insights. Data warehouses can scale up to petabytes in size. Common storage platforms include:
– **MPP architectures** – Massively parallel processing systems like Teradata allow scaling storage and compute power linearly.
– **SAN/NAS** – High bandwidth SANs and NAS appliances provide shared storage pools.
– **Object storage** – Distributed object stores allow cost-efficient scalability for vast amounts of unstructured data.
– **Cloud data lakes** – Platforms like AWS S3 and Azure Data Lake Storage for centralized analytics data.
The cloud in particular has become pivotal for data warehousing due to the ability to provision storage and compute elastically on demand. This removes limits on scalability. Snowflake and BigQuery are popular cloud-based data warehouse solutions.
Big Data Storage
“Big data” refers to collections of data so large and complex that traditional storage and processing techniques cannot effectively manage them. Big data often includes masses of unstructured data like server logs, social media content, photos, videos, sensor readings, and more. The volume, velocity, and variety of big data necessitates specialized storage platforms designed for scalability. Some examples include:
– **HDFS** – The Hadoop Distributed File System allows big data frameworks like MapReduce, Spark, and Hive to scale across commodity servers.
– **NoSQL databases** – Distributed NoSQL database systems like Cassandra, MongoDB, and Couchbase shard and replicate data across nodes.
– **Data lakes** – Highly scalable data lakes based on cloud object storage can ingest streams of raw data for analytics.
– **Data warehouses** – As mentioned above, some data warehouses now leverage various technologies to scale for big data.
For big data, having an architecture that can scale out across affordable commodity hardware is the key to cost-effective storage and analytics. Cloud infrastructure makes this vastly easier today than in the past.
Comparison of Options
Here is a summary comparison of some of the key data storage options discussed:
| Storage Type | Speed | Capacity | Cost |
|---|---|---|---|
| Local HDD | Slow | 100 GB – 10 TB | Cheap |
| Local SSD | Fast | 128 GB – 4 TB | Moderate |
| NAS | Fast | 100 TB – 50 PB | Moderate |
| SAN | Very Fast | 10 PB – 10 EB | Expensive |
| Cloud Storage | Fast | Unlimited | Cheap |
This comparison shows the range of performance, capacity, and economic costs for some of the popular storage mediums. The right option depends on the use case – whether its storing data locally on a desktop, sharing files on an office network, or accessing huge datasets in the cloud.
Conclusion
There are clearly many options available today for storing and managing data. Local storage like HDDs and SSDs works well for individual devices while networked and cloud storage better serve business scalability and accessibility needs. Key factors driving data storage decisions include:
– Required capacity
– Performance needs like speed and throughput
– Budget limitations
– Need for backups, redundancy, and disaster recovery
– Data security considerations
For small amounts of data, local and removable storage remains very common. As data sets grow larger, businesses typically shift to external NAS or SAN devices. For even larger scale needs, especially when leveraging big data analytics, cloud-based storage and databases have become the go-to solutions for most organizations today. The economics, agility and global accessibility of public cloud infrastructure makes it ideal for addressing virtually limitless storage.