Massive data storage, what are the ways and methods of massive data storage?

Sandstone MOS is an object storage product with both enterprise-level storage capabilities and intelligent retrieval and processing capabilities. The next-generation storage engine builds a cross-region storage architecture that can be scaled linearly with almost no capacity limit based on standard servers, providing highly reliable and high-availability service capabilities, integrating data intelligent processing and analysis capabilities, and simplifying the infrastructure required for massive data processing to greatly improve the efficiency of data processing.

Shanyan Massive Object Storage MOS, the optimal solution for massive unstructured data storage, adopts a decentralized and distributed technology architecture, supports tens of billions of files and exabyte-level capacity storage, and has efficient data retrieval, intelligent labeling and analysis capabilities, easily copes with the storage challenges of the big data and cloud era, and provides intelligent decision-making for enterprise development.

1. The capacity can be expanded linearly, and the single namespace can reach the exabyte level2. Massive small file storage, efficient access to tens of billions of files

Based on a fully distributed data and metadata storage architecture, Sandstone MOS is designed for massive small file storage, increasing the tens of millions of files stored in enterprise-level NAS to tens of billions of Internet-scale files, helping enterprises calmly cope with the challenges of massive small files growing geometrically.

3. The center is flexibly deployed, making disaster recovery, aggregation and distribution more convenient

Sandstone MOS supports flexible deployment of multiple data centers, providing customizable and flexible solutions for enterprise data disaster recovery, automatic switchover for disaster recovery, multi-branch, and nearby data access, helping enterprises achieve cross-region multi-active disaster recovery, data flow, and nearby read/write, helping businesses develop rapidly.

4. Support big data and AI, unified data storage and analysis

Sandstone MOS has a built-in intelligent file processing engine to realize batch processing functions including voice recognition, OCR recognition, file format conversion, etc., and can also realize voice and certificate retrieval in combination with tag retrieval capabilities, so as to help enterprises better manage unstructured data. At the same time, Sandstone MOS also supports docking with big data analysis platforms such as Hadoop and Spark, so that one set of storage can meet the needs of enterprise data storage, management and mining.

From the perspective of data storage mode, mass storage technology can be divided into two types: DAS (Direct Attached Storage) and Network Storage, of which Network Storage can be divided into NAS (Network Attached Storage) and SAN (Storage Area Net, WORK).

From the perspective of the composition of the data storage system, whether it is DAS, NAS or SAN, the storage system can be divided into three parts: the first is the disk array, which is the foundation of the storage system and the basic guarantee for completing data storage; The second is the connectivity and networking subsystem, through which one or more disk arrays are connected to the server; Finally, storage management software implements storage management tasks such as multiple server sharing and disaster prevention at the system and application level.

As mentioned above, the comprehensive survey information of land and resources remote sensing includes not only multi-source, multi-temporal, multi-scale, multi-resolution, multi-type remote sensing image data and basic geographic data, but also many observation and analysis data derived during the project development, and the data volume is very large. Therefore, according to the requirements of data sharing, in the process of data production, management, application services, update and maintenance, how to organize and manage these massive data, and how to access and obtain the required data quickly, comprehensively and effectively, have become prominent problems. Here, how to efficiently store and manage this data using existing large-scale commercial relational database systems has become the key to maximizing the performance of the system.

The storage and management of spatial data (data related to spatial location and spatial relationship) in traditional GIS systems mostly use these commercial software-specific file methods, such as ArcInfo coverage, MapInfo Tab, MapGIS WL, etc. If the amount of data is larger, the larger the file will be, the more complex the data processing will be, and the more difficult it will be to store, retrieve, and manage, and its biggest disadvantage is that it cannot perform multi-user concurrent operations.

It can be seen that it is obviously difficult to meet the requirements of using the traditional storage mechanism to manage massive data such as remote sensing comprehensive surveys. The spatial database engine technology developed in recent years is one of the ways to solve the problem of massive data storage management.

In the process of construction of this system, the spatial database engine arcSDE large relational database oracle combination technology is adopted, which ideally realizes the storage, retrieval, query and processing of massive data of remote sensing comprehensive survey. As we all know, Oracle provides a large-scale database environment, which can handle massive data well, and ArcSDE can load spatial and non-spatial data with geographic features into Oracle in a unified manner, therefore, through the ArcSDE spatial database engine, Oracle massive data management functions can be loaded into the GIS system, and Oracle's powerful management mechanism can be used for efficient transaction processing, record locking, concurrency control and other service operations.

Founded in 2007, Massive Data is a leading data technology service provider in China, covering system integration, technical services and product research and development of data technology. Headquartered in Beijing, the company has offices in Shenyang, Jinan, Shanghai, Nanjing, Wuhan, Guangzhou, Shenzhen, Chengdu, Xi'an and other cities, and has maintained a strong momentum of development since its establishment, with an average annual compound growth rate of more than 35%.

Founded in 2007, Beijing Massive Data Technology Co., Ltd. is a leading enterprise in China's data technology. For more than ten years, with the mission of "solving the problem of user database", we have focused on database product development, sales and service, and have two major database products:

Based on the open-source "AtlasDB" and the independent and controllable "Vastbase".

Massive Data has always adhered to independent technology research and development and innovation, and has a top domestic R&D team. Technical personnel account for more than 60% of the company's total number, of which the core technical personnel come from Oracle, IBM, HP, Teradata and other multinational technology companies. Massive Data has three R&D bases in Beijing, Hangzhou and Guangzhou, a provincial and ministerial-level enterprise technology center, and branches in major provincial capitals across the country, providing products and services for more than 2,000 large and medium-sized customers, covering key industries such as operators, finance, energy, power grids, and manufacturing.

Massive Data has established a standardized R&D, service and management system, and implemented strict quality control: a R&D management system has been established with CMMI standards, a quality assurance system has been established with ISO9001 standards, an information security management system has been established with ISO27000 standards, an information technology service management system has been established with ISO20000 standards, and an intellectual property management system has been established with GB29490 standards, so as to become a reliable partner in the data field for users.

The company is a second-class dealer, buying and selling. The company's management sales style thinking, the whole company is permeated with sales atmosphere, if you particularly want to do sales, you can try it, if you do something else, think twice.

There are many DBMS products, such as DB2, Oracle, MicrosoSqlServer, SybaseSqlServer, Informix, MySQL, etc., which have their own place in the database market.

The scope of middleware is very wide, and a variety of middleware products with different characteristics have emerged for different application needs. However, there is no precise definition of middleware so far, so the classification of middleware will be different from different angles or at different levels. Since the middlebook needs to shield the heterogeneous operating system and network protocols in the distributed environment, it must be able to provide communication services in the distributed environment, and this kind of communication state lease chain service is called a platform.

Depending on the purpose and implementation mechanism, platforms can be divided into the following main categories:

RemoteProcereCall: Message-oriented middleware

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