Storage organization for "open" sets of entity attributes in relational databases

Relations are practically implemented by database management systems in the form of two-dimensional tables. In this regard, certain difficulties arise in the development of relational database schemas, in which it is necessary to represent objects with an alterable (open) set of attributes. The article proposes a solution to this problem by including special relations in the scheme - relations of properties directory. Properties directory allow replenishing the sets of object attributes without changing the structure of the database. Examples of the practical use of properties directory in the development of database schemas of two information systems are presented.

Joy Arulraj Speaks Out on Non- Volatile Memory Database Systems

Welcome to this installment of the ACM SIGMOD Record's series of interviews with distinguished members of the database community. I'm Marianne Winslett, and today I have here with me Joy Arulraj, who won the 2019 ACM SIGMOD Jim Gray Dissertation Award for his thesis entitled The Design and Implementation of Non-volatile Memory Database Management Systems. Joy is now an Assistant Professor at Georgia Tech, and his PhD is from the Carnegie Mellon University, where he worked with Andy Pavlo, who won this same award in his time. So, Joy, welcome!

APPLYING NORMS, WEIGHTS AND MEASURES AS A QUERY SEARCH METHOD

В статье рассматривается возможность применения распределения потоков информации при работе в средах систем управления базами данных. Особое внимание уделяется использованию норм для дополнительной оптимизации последовательности поисковых запросов к массивам данных большого объема. In the article, the possibilities of distributing information flows when working in environments of database management systems. Particular attention is paid to the use of normal methods for optimizing search queries against a large amount of data.

CPU runtime optimization in data damage tracking quarantine and recovery (DTQR) scheme based on customized ANN

Database Management Systems (DBMS) are regularly used to store and process touchy endeavour information. In any case, it is beyond the realm of imagination to expect to verify the information by depending on the entrance control and security instruments of such frameworks alone; clients may handle their benefits or go around security systems to malevolently adjust and get to the information. Hence, we have developed a reliable, secure, and real-time data damage tracking Quarantine and recovery scheme using Customized ANN approach. The proposed DTQR scheme recovers the accurate data from any newer data and eliminates the fraudulent data. The approach also provides a solution for runtime problems occurring in the DBMS. Moreover, the proposed technique implemented in the working platform of JAVA and the results are analyzed with existing techniques to prove the efficiency of the proposed system.

A Newly Proposed Cloud Computing Based Strengthen Distributed Database System Model and Its Applications in Database Modelling

In the modern era of today’s exceptional Information age, the day to day transactions of huge sensitive data sets, which is in the form of PBs (Peta-Bytes) 250 bytes and YBs (Yotta – Bytes) 280 bytes are drastically increases with enormous speed on CLOUD data storage environment. CLOUDs data storage environment are one of the most superior and reliable platform for storing a large sets of data both at enterprise level or local level. Because CLOUD provides online data fetching capability to restore or fetching data at any geographical locations through login their correspondent credentials. But to enhancement or spread of these large data sets are becomes also very complex with respect to maintenance of these data with take concern of consistency and data security, because to maintain these large data sets with full of consistency and integrity are really a very typical and rational tasks, so here In this paper we proposed a distributed database management systems for CLOUD interface also preserves or to take concern data security features with full restoration of CIA (Confidentiality, Integrity, Availability or Authenticity) trade of Information Security. Here we also improvised the mechanisms of traditional distributed database management systems because the tendency to preserves information and recover ability after any misconceptions happens that we restore data which belongs to similar person may have to be stored at different locations, but this newly proposed distributed database systems architecture contains all information or record which belong to similar person are stored in one database rather restore it different databases but the location of these data have to be changes mean while that the content or data which resides in one databases have to be moved to some other database and also preserves the security features, and this model also have capability to run older traditional methodology based distributed database management systems using this model. So the detailed description about these models and communication infrastructure among different CLOUDs are append in the upcoming sections of this paper. Keywords: Cloud based Distributed Database system model, Distributed system, Distributed Database model of CLOUD, Cloud Distributed Database, CLOUD based database systems

HTAP With Reactive Streaming ETL

In database management systems (DBMSs), query workloads can be classified as online transactional processing (OLTP) or online analytical processing (OLAP). These often run within separate DBMSs. In hybrid transactional and analytical processing (HTAP), both workloads may execute within the same DBMS. This article shows that it is possible to run separate OLTP and OLAP DBMSs, and still support timely business decisions from analytical queries running off fresh transactional data. Several setups to manage OLTP and OLAP workloads are analysed. Then, benchmarks on two industry standard DBMSs empirically show that, under an OLTP workload, a row-store DBMS sustains a 1000 times higher throughput than a columnar DBMS, whilst OLAP queries are more than 4 times faster on a columnar DBMS. Finally, a reactive streaming ETL pipeline is implemented which connects these two DBMSs. Separate benchmarks show that OLTP events can be streamed to an OLAP database within a few seconds.

HTAP With Reactive Streaming ETL

In database management systems (DBMSs), query workloads can be classified as online transactional processing (OLTP) or online analytical processing (OLAP). These often run within separate DBMSs. In hybrid transactional and analytical processing (HTAP), both workloads may execute within the same DBMS. This article shows that it is possible to run separate OLTP and OLAP DBMSs, and still support timely business decisions from analytical queries running off fresh transactional data. Several setups to manage OLTP and OLAP workloads are analysed. Then, benchmarks on two industry standard DBMSs empirically show that, under an OLTP workload, a row-store DBMS sustains a 1000 times higher throughput than a columnar DBMS, whilst OLAP queries are more than 4 times faster on a columnar DBMS. Finally, a reactive streaming ETL pipeline is implemented which connects these two DBMSs. Separate benchmarks show that OLTP events can be streamed to an OLAP database within a few seconds.