Data Storage – the type of big data technology comprises infrastructure designed to fetch, store, and manage big data. Data is organized in a manner that allows easy access, usage, and processing by various programs.
Data storage refers to the method of saving digital information in a systematic way, enabling easy access, management, and protection of data for future use. It is crucial in technology, business operations, and personal data management, where different types of storage solutions serve diverse needs.
Types of Data Storage
- Primary Storage: Often called volatile storage, primary storage includes Random Access Memory (RAM) and cache. It temporarily holds data that is actively being used or processed. For example, when you run an application on your computer, it relies on RAM for quick access to data. Once the device shuts down, the data in RAM is erased.
- Secondary Storage: This refers to non-volatile storage that retains data even when the device is powered off. Examples include hard disk drives (HDDs), solid-state drives (SSDs), USB drives, CDs, and DVDs. Secondary storage is ideal for long-term data preservation and backups.
- Cloud Storage: Cloud storage is an internet-based service that allows data to be stored on remote servers managed by a cloud service provider. Popular examples include Google Drive, Dropbox, Amazon S3, and Microsoft OneDrive. This option offers scalability, accessibility from any device with an internet connection, and robust backup and security measures.
- Network Attached Storage (NAS): NAS refers to a dedicated storage device connected to a network, providing centralized and shared storage for multiple users and devices. Businesses use NAS systems to improve data management and access efficiency. Examples of NAS include Synology DiskStation and QNAP.
- Databases: Databases store large amounts of structured data that can be accessed and managed easily. Examples include SQL databases like MySQL, Oracle Database, and NoSQL databases such as MongoDB. They are used in applications that require complex data handling, like customer relationship management (CRM) and financial software.
- Tape Storage: Often used for archival and backup purposes, tape storage involves magnetic tape reels that store large volumes of data at a lower cost. Though slower in data retrieval, it remains a viable option for long-term data storage in organizations.
Examples of Data Storage
- Hard Disk Drives (HDDs): These are traditional storage devices that use spinning magnetic disks to store data. They are commonly found in desktops, laptops, and servers. While HDDs are cost-effective, they are slower compared to SSDs.
- Solid-State Drives (SSDs): SSDs use flash memory to store data and are significantly faster than HDDs. They are often used in modern laptops, gaming consoles, and high-performance servers. Although more expensive, SSDs provide quick access to data, enhancing system speed and reliability.
- USB Flash Drives: Portable and convenient, USB drives are used for transferring and storing smaller amounts of data. They are popular for personal use, providing an easy way to carry documents, photos, and videos.
- Google Drive: A cloud-based storage service, Google Drive allows users to store and share files online. It offers both free and paid plans, making it a practical option for individuals and businesses looking for accessible and secure data storage.
- Amazon S3: Amazon’s Simple Storage Service (S3) provides scalable cloud storage for developers and enterprises. It is used for hosting websites, backing up data, and archiving information. S3 ensures data durability and availability, making it a key resource for cloud applications.
- NAS Systems: In a home or office setting, NAS systems like Synology or QNAP provide a centralized way to store and share data across multiple devices. They are valuable for data backup, media streaming, and collaborative work.
- Optical Discs (CDs and DVDs): Once widely used for storing music, software, and movies, CDs and DVDs have been largely replaced by more advanced storage methods. However, they are still utilized for distributing software and archival storage.
Data storage is foundational in today’s data-driven world, enabling everything from routine computing tasks to enterprise-level data management.
Some of the top big data tools for this type of work with data include:
Hadoop technologies
The Hadoop technology stack comes with a framework for distributed storage & big data processing using the MapReduce programming model. Some of the perks of this Apache big data stack include its ability to quickly manage distributed data (store and process) at reasonable costs. Big data technologies like Hadoop are scalable, resilient to failure, and very flexible. The downsides of Hadoop include poor security, low performance with fewer big data files, & the ability to support batch processing only, etc. You can use big data technologies spark tools as an alternative to the Hadoop technology stack.
MongoDB
MongoDB is one of the big data database technologies – a NoSQL program that uses documents similar to JSON. It provides an alternative schema to that of Relational Databases. This enables it to handle several data types that come in vast amounts across Distributed Architectures. The main advantages of MongoDB are flexibility and scalability. This is because it is easy to utilize replica sets on this big data database. On the other hand, MongoDB has the weakness of low speed and increased data size.
Rainstor
This is a Database Management System software that handles big data for businesses. It can eliminate duplicate files as it sorts out and stores huge volumes of information for reference. The latest version of this software can handle big data sets with high ingest rates. Also, it comes with multi-tenancy features and supports cloud storage. Rainstor can shrink large data for storage in the cloud. A terabyte can be reduced to 25GB. Other perks of Rainstor include lower costs.
