How to store big data sets?
The major element of the Fourth Industrial Revolution is information and its importance in development. Every company, institution, and organization create massive amounts of data nowadays. Efficient management is crucial. What can we do to make it more accessible, effective, and profitable? Learn more about how to store big data sets!
Where are large datasets stored?
Big Data (for e.g. satellite data, videos, or IoT data) must be stored with help of specialized programs because often it has an unstructured form. The system can split the huge data into blocks and distribute them in the cluster nodes. Most of the IT tools of this kind run with cloud technology, which can provide the necessary computing power and sufficient capacity.
Many research projects developed in recent years have proven the importance of accessibility for technology for storing, managing, and processing Big Data. Storing and dissemination of heterogeneous data can be a serious technical challenge. Not every company can invest in IT infrastructure that could manage this.
Object storage is an economical, easily scalable, and generally available solution. It allows to store unstructured or extremely diverse data, without a hierarchical directory structure. Object storage uses a unique identifier for each object, which allows massive and dynamic scaling. This solution should be applied in practice to automate the process of data storage and sharing as much as possible.
More information about how Big Data is stored can be found here: https://cloudferro.com/en/eo-cloud/storage-big-data/.
What is the best way to store large data sets?
The efficient storage of data requires a secure cloud-native platform. One of the best options in Europe is CERODIAS, which currently stores almost 21 PB of Earth Observation data and processes around 25 TB of data daily.
CERODIAS supports data in the cloud and outside it because of open source CEPH software for building mass storage. It enables building and managing object-oriented storage for OpenStack, providing advanced cataloguing solutions, incl. CERODIAS FINDER graphic application and many other interfaces. This allows interested stakeholders to use the data in an automated manner.
The operator of CERODIAS is CloudFerro, a Polish company specialized in cloud services. It recently ran tests that showed it could manage 2PB of data per day from its repositories and currently provides 21 PB of EO data (possible increase to 50 PB). Benchmarking and test results as well as experience in building and operating multiple cloud platforms (for e.g. Climate Data Store, CODE-DE, WEkEO, EO IPT) make this option useful to great initiatives such as Destination Earth.
CloudFerro thanks to the knowledge and experience of previous projects can acquire, store, index, and distribute massive amounts of EO data. It can provide easy, remote, broadband, and scalable access to online, granular data in a cost-efficient manner.
More information on Big Data storage and the full CloudFerro offer can be found at: https://cloudferro.com/en/.