IT: Blockchain (Definitions)

"A block chain is a perfect place to store value, identities, agreements, property rights, credentials, etc. Once you put something like a Bit coin into it, it will stay there forever. It is decentralized, disinter mediated, cheap, and censorship-resistant." (Kirti R Bhatele et al, "The Role of Artificial Intelligence in Cyber Security", 2019)

"A system made-up of blocks that are used to record transactions in a peer-to-peer cryptocurrency network such as bitcoins." (Murad Al Shibli, "Hybrid Artificially Intelligent Multi-Layer Blockchain and Bitcoin Cryptology", 2020)

"A chain of blocks containing data that is bundled together. This database is shared across a network of computers (so-called distributed ledger network). Each data block links to the previous block in the blockchain through a cryptographic hash of the previous block, a timestamp, and transaction data. The blockchain only allows data to be written, and once that data has been accepted by the network, it cannot be changed." (Jurij Urbančič et al, "Expansion of Technology Utilization Through Tourism 4.0 in Slovenia", 2020)

"A system in which a record of transactions made in Bitcoin or another cryptocurrency is maintained across several computers that are linked in a peer-to-peer network. Amany M Alshawi, "Decentralized Cryptocurrency Security and Financial Implications: The Bitcoin Paradigm", 2020)

"An encrypted ledger that protects transaction data from modification." (David T A Wesley, "Regulating the Internet, Encyclopedia of Criminal Activities and the Deep Web", 2020)

"Blockchain is a decentralized, immutable, secure data repository or digital ledger where the data is chronologically recorded. The initial block named as Genesis. It is a chain of immutable data blocks what has anonymous individuals as nodes who can transact securely using cryptology. Blockchain technology is subset of distributed ledger technology." (Umit Cali & Claudio Lima, "Energy Informatics Using the Distributed Ledger Technology and Advanced Data Analytics", 2020)

"Blockchain is a meta-technology interconnected with other technologies and consists of several architectural layers: a database, a software application, a number of computers connected to each other, peoples’ access to the system and a software ecosystem that enables development. The blockchain runs on the existing stack of Internet protocols, adding an entire new tier to the Internet to ensure economic transactions, both instant digital currency payments and complicated financial contracts." (Aslı Taşbaşı et al, "An Analysis of Risk Transfer and Trust Nexus in International Trade With Reference to Turkish Data", 2020) 

"Is a growing list of records, called blocks, which are linked using cryptography. Each block contains a cryptographic hash of the previous block a timestamp, and transaction data. (Vardan Mkrttchian, "Perspective Tools to Improve Machine Learning Applications for Cyber Security", 2020)

"This is viewed as a mechanism to provide further protection and enhance the security of data by using its properties of immutability, auditability and encryption whilst providing transparency amongst parties who may not know each other, so operating in a trustless environment." (Hamid Jahankhani & Ionuț O Popescu, "Millennials vs. Cyborgs and Blockchain Role in Trust and Privacy", 2020)

"A blockchain is a data structure that represents the record of each accounting move. Each account transaction is signed digitally to protect its authenticity, and no one can intervene in this transaction." (Ebru E Saygili & Tuncay Ercan, "An Overview of International Fintech Instruments Using Innovation Diffusion Theory Adoption Strategies", 2021)

"A system in which a record of transactions made in bitcoin or another cryptocurrency are maintained across several computers that are linked in a peer-to-peer network." (Silvije Orsag et al, "Finance in the World of Artificial Intelligence and Digitalization", 2021)

"It is a decentralized computation and information sharing platform that enables multiple authoritative domains, who don’t trust each other, to cooperate, coordinate and collaborate in a rational decision-making process." (Vinod Kumar & Gotam Singh Lalotra, "Blockchain-Enabled Secure Internet of Things", 2021)

"A concept consisting of the methods, technologies, and tool sets to support a distributed, tamper-evident, and reliable way to ensure transaction integrity, irrefutability, and non-repudiation. Blockchains are write-once, append-only data stores that include validation, consensus, storage, replication, and security for transactions or other records." (Forrester)

[hybrid blockchain:] "A network with a combination of characteristics of public and private blockchains where a blockchain may incorporate select privacy, security and auditability elements required by the implementation." (AICPA)

[private blockchain:] "A restricted access network controlled by an entity or group which is similar to a traditional centralized network." (AICPA)

"A technology that records a list of records, referred to as blocks, that are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp and transaction data." (AICPA)

[public blockchain:] "An open network where participants can view, read and write data, and no one participant has control (e.g., Bitcoin, Ethereum)." (AICPA)

Data Warehousing: Operational Data Store (Definitions)

"The operational data store is subject-oriented and contains current, integrated, consistent data that reflects the current state of its subject. Operational data stores are similar to enterprise data warehouses in that they may include data from different systems that has been made consistent. Operational data stores are different from enterprise data warehouses in that they are updated frequently to reflect the current state of the operational systems." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"A physical set of tables sitting between the operational systems and the data warehouse or a specially administered hot partition of the data warehouse itself. The main reason for an ODS is to provide immediate reporting of operational results if neither the operational system nor the regular data warehouse can provide satisfactory access. Because an ODS is necessarily an extract of the operational data, it also may play the role of source for the data warehouse." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The operational data store is a subject-oriented, integrated, current, volatile collection of data used to support the operational and tactical decision-making process for the enterprise. It is the central point of data integration for business management, delivering a common view of enterprise data." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A hybrid structure designed to support both operational transaction processing and analytical processing." (William H Inmon, "Building the Data Warehouse", 2005)

"A collection of data from operational systems, most often integrated together, that is used for some operational purpose. The most critical characteristic here is that this is used for some operational function. This operational dependency takes precedence and the ODS should not be considered a central component of the data warehousing environment. An ODS can be a clean, integrated source of data to be pulled into the data warehousing environment." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"A database designed to integrate data from multiple sources to facilitate operations. This is as opposed to a data warehouse, which integrates data from multiple sources to facilitate reporting and analysis." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A database that is subject-oriented, read-only to end users, current (non-historical), volatile, and integrated; is separate from and derived from one or more systems of record; and supports day-today business operations and real-time decision making." (David Lyle & John G Schmidt, "Lean Integration", 2010)

"A DB system designed to integrate data from multiple sources to allow operational access to the data for operational reporting." (Martin Oberhofer et al, "The Art of Enterprise Information Architecture", 2010)

"Database for transaction processing systems that uses data warehouse concepts to provide clean data." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"A database designed to integrate data from multiple sources for additional operations on the data." (Craig S Mullins, "Database Administration", 2012)

"A data store that provides data from the original source in near real time." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"ODS is the decision support database that integrated operational data from multiple source systems used to capture operational data and is used primarily for near real time operational reporting and analytics. ODSs are used to measure the operations processes efficiencies. The integration pattern is at the lowest levels of granularity and can happen from near real-time to multiple times in a day." (Saumya Chaki, "Enterprise Information Management in Practice", 2015)

"A data store that integrates data from a range of sources, which is subsequently merged and cleaned to serve as the foundation for enterprise operational reporting. It is an important piece of an Enterprise Data Warehouse (EDW) used for enterprise analytical reporting." (David K Pham, "From Business Strategy to Information Technology Roadmap", 2016)

"An ODS system integrates operational or transactional data from multiple systems to support operational reporting." (John D Kelleher & Brendan Tierney, "Data science", 2018)

"An operational data store (ODS) is an alternative to having operational decision support system (DSS) applications access data directly from the database that supports transaction processing (TP). While both require a significant amount of planning, the ODS tends to focus on the operational requirements of a particular business process (for example, customer service), and on the need to allow updates and propagate those updates back to the source operational system from which the data elements were obtained. The data warehouse, on the other hand, provides an architecture for decision makers to access data to perform strategic analysis, which often involves historical and cross-functional data and the need to support many applications." (Gartner)

DBMS: NoSQL (Definitions)

"An umbrella term for non-relational data stores, hence the name. These stores sacrifice ACID transactions for greater scalability and availability." (Dean Wampler, "Functional Programming for Java Developers", 2011)

"A set of technologies that created a broad array of database management systems that are distinct from relational database systems. One major difference is that SQL is not used as the primary query language. These database management systems are also designed for distributed data stores." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A class of database management systems that consist of non-relational, distributed data stores. These systems are optimized for supporting the storage and retrieval requirements of massive-scale data-intensive applications." (IBM, "Informix Servers 12.1", 2014)

"A database that doesn’t adhere to relational database structures. Used to organize and query unstructured data." (Jason Williamson, "Getting a Big Data Job For Dummies", 2015)

"Any of a class of database management systems that reject the limitations and drawbacks dictated by, or associated with, the relational model. NoSQL products tend to specialize in a single or limited number of areas, such as high-performance processing, big data (giga-record systems), diverse data types (video, pictures, mathematical models), documents, and so on. Their specialized focus often requires deemphasizing other areas such as data consistency and backup and recovery." (George Tillmann, "Usage-Driven Database Design: From Logical Data Modeling through Physical Schmea Definition", 2017)

"In general, NoSQL databases provide a mechanism for storage and retrieval of data modeled in means other than the tabular relations used in relational databases." (Prashant Natarajan et al, "Demystifying Big Data and Machine Learning for Healthcare", 2017)

"NoSQL means 'not only SQL' or 'no SQL at all'. Being a new type of non-relational databases, NoSQL databases are developed for efficient and scalable management of big data." (Zongmin Ma & Li Yan, "Towards Massive RDF Storage in NoSQL Databases: A Survey", 2019)

"A broad term for a set of data access technologies that do not use the SQL language as their primary mechanism for reading and writing data. Some NoSQL technologies act as key-value stores, only accepting single-value reads and writes; some relax the restrictions of the ACID methodology; still others do not require a pre-planned schema." (MySQL, "MySQL 8.0 Reference Manual Glossary")

"A NoSQL database is distinguished mainly by what it is not - it is not a structured relational database format that links multiple separate tables. NoSQL stands for 'not only SQL', meaning that SQL, or structured query language is not needed to extract and organize information. NoSQL databases tend to be more diverse and flatter than relational databases (in a flat database, all data is contained in the same, large table)." (Statistics.com)

"NoSQL is a database management system built for the complexities of working with Big Data. Unlike SQL, NoSQL does not store data in a relational format." (Xplenty) [source]

"No-SQL (aka not only SQL) database systems are distributed, non-relational databases designed for large-scale data storage and for massively-parallel data processing across a large number of commodity servers." (IBM) 

"NoSQL is short for 'not only SQL'. NoSQL databases include mechanisms for storage and retrieval of data based on means other than the tabular relations used in relational databases." (Idera) [source]

"sometimes referred to as ‘Not only SQL’ as it is a database that doesn’t adhere to traditional relational database structures. It is more consistent and can achieve higher availability and horizontal scaling." (Analytics Insight)

DBMS: Repository (Definitions)

"The storage container for the metadata managed by OLAP Services. Metadata is stored in tables in a relational database and is used to define the parameters and properties of OLAP server objects." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A database containing information models that, in conjunction with the executable software, manage the database." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A repository is a collection of resources that can be accessed to retrieve information." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A database for software and components, with an emphasis on revision control and configuration management. Where they keep the good stuff, in other words." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"A database containing information models that, in conjunction with the executable software, manage the database." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A store of information about the data assets of an organization." (Craig S Mullins, "Database Administration", 2012)

"A database for software and components, with an emphasis on revision control and configuration management (where they keep the good stuff, in other words)." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A place where important corporate metadata is stored" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"a database for software and components, with an emphasis on revision control and configuration management (where they keep the good stuff, in other words)." (Judith S Hurwitz, "Cognitive Computing and Big Data Analytics", 2015)

"A storage location for physical data, preferably databases." (Hamid R Arabnia et al, "Application of Big Data for National Security", 2015)

"In a software context, a repository is a data store that contains the code and or data for a project." (Alex Thomas, "Natural Language Processing with Spark NLP", 2020)

"A database containing information models that, in conjunction with the executable software, manage the database." (Microsoft Technet)