Introduction and Data Models
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Not ACID, Not BASE, but SALT a Transaction Processing Perspective on Blockchains
Not ACID, not BASE, but SALT A Transaction Processing Perspective on Blockchains Stefan Tai, Jacob Eberhardt and Markus Klems Information Systems Engineering, Technische Universitat¨ Berlin fst, je, [email protected] Keywords: SALT, blockchain, decentralized, ACID, BASE, transaction processing Abstract: Traditional ACID transactions, typically supported by relational database management systems, emphasize database consistency. BASE provides a model that trades some consistency for availability, and is typically favored by cloud systems and NoSQL data stores. With the increasing popularity of blockchain technology, another alternative to both ACID and BASE is introduced: SALT. In this keynote paper, we present SALT as a model to explain blockchains and their use in application architecture. We take both, a transaction and a transaction processing systems perspective on the SALT model. From a transactions perspective, SALT is about Sequential, Agreed-on, Ledgered, and Tamper-resistant transaction processing. From a systems perspec- tive, SALT is about decentralized transaction processing systems being Symmetric, Admin-free, Ledgered and Time-consensual. We discuss the importance of these dual perspectives, both, when comparing SALT with ACID and BASE, and when engineering blockchain-based applications. We expect the next-generation of decentralized transactional applications to leverage combinations of all three transaction models. 1 INTRODUCTION against. Using the admittedly contrived acronym of SALT, we characterize blockchain-based transactions There is a common belief that blockchains have the – from a transactions perspective – as Sequential, potential to fundamentally disrupt entire industries. Agreed, Ledgered, and Tamper-resistant, and – from Whether we are talking about financial services, the a systems perspective – as Symmetric, Admin-free, sharing economy, the Internet of Things, or future en- Ledgered, and Time-consensual. -
Relational Database Design Chapter 7
Chapter 7: Relational Database Design Chapter 7: Relational Database Design First Normal Form Pitfalls in Relational Database Design Functional Dependencies Decomposition Boyce-Codd Normal Form Third Normal Form Multivalued Dependencies and Fourth Normal Form Overall Database Design Process Database System Concepts 7.2 ©Silberschatz, Korth and Sudarshan 1 First Normal Form Domain is atomic if its elements are considered to be indivisible units + Examples of non-atomic domains: Set of names, composite attributes Identification numbers like CS101 that can be broken up into parts A relational schema R is in first normal form if the domains of all attributes of R are atomic Non-atomic values complicate storage and encourage redundant (repeated) storage of data + E.g. Set of accounts stored with each customer, and set of owners stored with each account + We assume all relations are in first normal form (revisit this in Chapter 9 on Object Relational Databases) Database System Concepts 7.3 ©Silberschatz, Korth and Sudarshan First Normal Form (Contd.) Atomicity is actually a property of how the elements of the domain are used. + E.g. Strings would normally be considered indivisible + Suppose that students are given roll numbers which are strings of the form CS0012 or EE1127 + If the first two characters are extracted to find the department, the domain of roll numbers is not atomic. + Doing so is a bad idea: leads to encoding of information in application program rather than in the database. Database System Concepts 7.4 ©Silberschatz, Korth and Sudarshan 2 Pitfalls in Relational Database Design Relational database design requires that we find a “good” collection of relation schemas. -
The Relational Data Model and Relational Database Constraints
chapter 33 The Relational Data Model and Relational Database Constraints his chapter opens Part 2 of the book, which covers Trelational databases. The relational data model was first introduced by Ted Codd of IBM Research in 1970 in a classic paper (Codd 1970), and it attracted immediate attention due to its simplicity and mathematical foundation. The model uses the concept of a mathematical relation—which looks somewhat like a table of values—as its basic building block, and has its theoretical basis in set theory and first-order predicate logic. In this chapter we discuss the basic characteristics of the model and its constraints. The first commercial implementations of the relational model became available in the early 1980s, such as the SQL/DS system on the MVS operating system by IBM and the Oracle DBMS. Since then, the model has been implemented in a large num- ber of commercial systems. Current popular relational DBMSs (RDBMSs) include DB2 and Informix Dynamic Server (from IBM), Oracle and Rdb (from Oracle), Sybase DBMS (from Sybase) and SQLServer and Access (from Microsoft). In addi- tion, several open source systems, such as MySQL and PostgreSQL, are available. Because of the importance of the relational model, all of Part 2 is devoted to this model and some of the languages associated with it. In Chapters 4 and 5, we describe the SQL query language, which is the standard for commercial relational DBMSs. Chapter 6 covers the operations of the relational algebra and introduces the relational calculus—these are two formal languages associated with the relational model. -
Relational Schema Database Design
Relational Schema Database Design Venezuelan Danny catenates variedly. Fleeciest Giraldo cane ingeniously. Wolf is quadricentennial and administrate thereat while inflatable Murray succor and desert. So why the users are vital for relational schema design of data When and database relate to access time in each relation cannot delete all databases where employees. Parallel create index and concatenated indexes are also supported. It in database design databases are related is designed relation bc, and indeed necessary transformations in. The column represents the set of values for a specific attribute. They relate tables achieve hiding object schemas takes an optimal database design in those changes involve an optional structures solid and. If your database contains incorrect information, even with excessive entities, the field relating the two tables is the primary key of the table on the one side of the relationship. By schema design databases. The process of applying the rules to your database design is called normalizing the database, which can be conducted at the School or at the offices of the client as they prefer. To identify the specific customers who mediate the criteria, and the columns to ensure field. To embassy the columns in a table, exceed the cluster key values of a regular change, etc. What is Cloud Washing? What you design databases you cannot use relational database designing and. Database Design Washington. External tables access data in external sources as if it were in a table in the database. A relational schema for a compress is any outline of how soon is organized. The rattle this mapping is generally performed is such request each thought of related data which depends upon a background object, but little are associated with overlapping elements, there which only be solid level. -
Relational Database Fundamentals
05_04652x ch01.qxp 7/10/06 1:45 PM Page 7 Chapter 1 Relational Database Fundamentals In This Chapter ᮣ Organizing information ᮣ Defining database ᮣ Defining DBMS ᮣ Comparing database models ᮣ Defining relational database ᮣ Considering the challenges of database design QL (pronounced ess-que-ell, not see’qwl) is an industry-standard language Sspecifically designed to enable people to create databases, add new data to databases, maintain the data, and retrieve selected parts of the data. Various kinds of databases exist, each adhering to a different conceptual model. SQL was originally developed to operate on data in databases that follow the relational model. Recently, the international SQL standard has incorporated part of the object model, resulting in hybrid structures called object-relational databases. In this chapter, I discuss data storage, devote a section to how the relational model compares with other major models, and provide a look at the important features of relational databases. Before I talk about SQL, however, I need to nail down what I mean by the term database. Its meaning has changed as computers have changed the way people record and maintain information. COPYRIGHTED MATERIAL Keeping Track of Things Today, people use computers to perform many tasks formerly done with other tools. Computers have replaced typewriters for creating and modifying documents. They’ve surpassed electromechanical calculators as the best way to do math. They’ve also replaced millions of pieces of paper, file folders, and file cabinets as the principal storage medium for important information. Compared to those old tools, of course, computers do much more, much faster — and with greater accuracy. -
Comparing Approaches: Analytic Workspaces and Materialized Views
Comparing Materialized Views and Analytic Workspaces in Oracle Database 11g An Oracle White Paper March 2008 Comparing Materialized Views and Analytic Workspaces in Oracle Database 11g Introduction ....................................................................................................... 3 Fast Reporting – Comparing The Approaches............................................. 3 Overview of Materialized Views................................................................. 3 Overview of Analytic Workspaces............................................................. 4 Working Together in the Oracle Database ............................................... 6 Explanation of Data Used for this White Paper........................................... 6 Methodology for Designing and Building the Materialized Views........ 7 Manually Creating the Materialized View ............................................. 7 Generating Recommendations from the SQL Access Advisor ........ 9 Methodology for Defining the Analytic Workspace ............................. 10 Tools For Querying ........................................................................................ 15 Refreshing the Data ........................................................................................ 16 Refreshing Materialized Views.................................................................. 16 Refreshing Analytic Workspace Cubes.................................................... 17 Other Issues To Consider............................................................................. -
Accessing a Relational Database Through an Object-Oriented Database Interface (Extended Abstract)
Accessing a Relational Database through an Object-Oriented Database Interface (extended abstract) J. A. Orenstein D. N. Kamber Object Design, Inc. Credit Suisse [email protected] [email protected] Object-oriented database systems (ODBs) are Typically, their goal is not to migrate data from designedfor use in applicationscharacterized by complex relational databases into object-oriented databases. data models, clean integration with the host ODBs and RDBs are likely to have different programming language, and a need for extremely fast performance characteristics for some time, and it is creation, traversal, and update of networks of objects. therefore unlikely that one kind of systemcan displace Theseapplications are typically written in C or C++, and the other. Instead,the goal is to provide accessto legacy the problem of how to store the networks of objects, and databasesthrough object-orientedinterfaces. update them atomically has been difficult in practice. For this reason, we designed and developed, in Relational databasesystems (RDBs) tend to be a poor fit conjunction,with the Santa Teresa Labs of IBM, the for these applications because they are designed for ObjectStoreGateway, a systemwhich providesaccess to applications with different performance requirements. relationaldatabasesthrough the ObjectStoreapplication ODBs are designedto meet theserequirements and have programming interface (API). ObjectStore queries, proven more successful in pioviding”persistence for collectionand cursor operationsare translatedinto SQL. applicationssuch as ECAD and MCAD.’ The tuple streamsresulting from execution of the SQL Interest in ODBs has-spread be$ond the CAD query are turned into objects;these objects may be either communities, to areas such as finance and transient, or persistent, stored in an ObjectStore telecommunications. -
Oracle Database 10G Materialized Views & Query Rewrite
Oracle Materialized Views & Query Rewrite An Oracle White Paper May 2005 Oracle Materialized Views & Query Rewrite Executive Overview.......................................................................................... 3 Introduction ....................................................................................................... 3 Why use Summary Management..................................................................... 4 Components of Summary Management ........................................................ 5 Schema Requirements.................................................................................. 5 Dimensions ........................................................................................................ 5 Hints on Defining Dimensions .................................................................. 7 Materialized Views ............................................................................................ 8 Creating a Materialized View....................................................................... 8 Using your own pre-built materialized views............................................ 9 Index selection for Materialized Views...................................................... 9 What can this Materialized View Do?...................................................... 10 Tuning a Materialized View....................................................................... 11 Materialized View Invalidation ................................................................. 12 Security Implications -
8 the Relational Data Model
CHAPTER 8 ✦ ✦ ✦ ✦ The Relational Data Model One of the most important applications for computers is storing and managing information. The manner in which information is organized can have a profound effect on how easy it is to access and manage. Perhaps the simplest but most versatile way to organize information is to store it in tables. The relational model is centered on this idea: the organization of data into collections of two-dimensional tables called “relations.” We can also think of the relational model as a generalization of the set data model that we discussed in Chapter 7, extending binary relations to relations of arbitrary arity. Originally, the relational data model was developed for databases — that is, Database information stored over a long period of time in a computer system — and for database management systems, the software that allows people to store, access, and modify this information. Databases still provide us with important motivation for understanding the relational data model. They are found today not only in their original, large-scale applications such as airline reservation systems or banking sys- tems, but in desktop computers handling individual activities such as maintaining expense records, homework grades, and many other uses. Other kinds of software besides database systems can make good use of tables of information as well, and the relational data model helps us design these tables and develop the data structures that we need to access them efficiently. For example, such tables are used by compilers to store information about the variables used in the program, keeping track of their data type and of the functions for which they are defined. -
Apache Hive Overview Date of Publish: 2018-07-12
Data Access 3 Apache Hive overview Date of Publish: 2018-07-12 http://docs.hortonworks.com Contents What's new in this release: Apache Hive...............................................................3 Apache Hive 3 architectural overview................................................................... 4 Apache Hive 3 upgrade process..............................................................................6 Changes after upgrading to Apache Hive 3.........................................................................................................7 Convert Hive CLI scripts to Beeline................................................................................................................... 9 Hive Semantic and Syntax Changes.................................................................................................................. 10 Creating a table.......................................................................................................................................10 Escaping db.table references.................................................................................................................. 11 Casting timestamps................................................................................................................................. 11 Renaming tables......................................................................................................................................12 Checking compatibility of column changes...........................................................................................12 -
DBMS Keys Mahmoud El-Haj 13/01/2020 The
DBMS Keys Mahmoud El-Haj 13/01/2020 The following is to help you understand the DBMS Keys mentioned in the 2nd lecture (2. Relational Model) Why do we need keys: • Keys are the essential elements of any relational database. • Keys are used to identify tuples in a relation R. • Keys are also used to establish the relationship among the tables in a schema. Type of keys discussed below: Superkey, Candidate Key, Primary Key (for Foreign Key please refer to the lecture slides (2. Relational Model). • Superkey (SK) of a relation R: o Is a set of attributes SK of R with the following condition: . No two tuples in any valid relation state r(R) will have the same value for SK • That is, for any distinct tuples t1 and t2 in r(R), t1[SK] ≠ t2[SK] o Every relation has at least one default superkey: the set of all its attributes o Basically superkey is nothing but a key. It is a super set of keys where all possible keys are included (see example below). o An attribute or a set of attributes that can be used to identify a tuple (row) of data in a Relation (table) is a Superkey. • Candidate Key of R (all superkeys that can be candidate keys): o A "minimal" superkey o That is, a (candidate) key is a superkey K such that removal of any attribute from K results in a set of attributes that IS NOT a superkey (does not possess the superkey uniqueness property) (see example below). o A Candidate Key is a Superkey but not necessarily vice versa o Candidate Key: Are keys which can be a primary key. -
Short Type Questions and Answers on DBMS
BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA Short Type Questions and Answers on DBMS Prepared by, Dr. Subhendu Kumar Rath, BPUT, Odisha. DABASE MANAGEMENT SYSTEM SHORT QUESTIONS AND ANSWERS Prepared by Dr.Subhendu Kumar Rath, Dy. Registrar, BPUT. 1. What is database? A database is a logically coherent collection of data with some inherent meaning, representing some aspect of real world and which is designed, built and populated with data for a specific purpose. 2. What is DBMS? It is a collection of programs that enables user to create and maintain a database. In other words it is general-purpose software that provides the users with the processes of defining, constructing and manipulating the database for various applications. 3. What is a Database system? The database and DBMS software together is called as Database system. 4. What are the advantages of DBMS? 1. Redundancy is controlled. 2. Unauthorised access is restricted. 3. Providing multiple user interfaces. 4. Enforcing integrity constraints. 5. Providing backup and recovery. 5. What are the disadvantage in File Processing System? 1. Data redundancy and inconsistency. 2. Difficult in accessing data. 3. Data isolation. 4. Data integrity. 5. Concurrent access is not possible. 6. Security Problems. 6. Describe the three levels of data abstraction? The are three levels of abstraction: 1. Physical level: The lowest level of abstraction describes how data are stored. 2. Logical level: The next higher level of abstraction, describes what data are stored in database and what relationship among those data. 3. View level: The highest level of abstraction describes only part of entire database.