Performance Analysis of Nosql and Relational Databases with Couchdb and Mysql for Application’S Data Storage
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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. -
MDA Process to Extract the Data Model from a Document-Oriented Nosql Database Amal Ait Brahim, Rabah Tighilt Ferhat, Gilles Zurfluh
MDA process to extract the data model from a document-oriented NoSQL database Amal Ait Brahim, Rabah Tighilt Ferhat, Gilles Zurfluh To cite this version: Amal Ait Brahim, Rabah Tighilt Ferhat, Gilles Zurfluh. MDA process to extract the data model from a document-oriented NoSQL database. ICEIS 2019: 21st International Conference on Enterprise Information Systems, May 2019, Heraklion, Greece. pp.141-148, 10.5220/0007676201410148. hal- 02886696 HAL Id: hal-02886696 https://hal.archives-ouvertes.fr/hal-02886696 Submitted on 1 Jul 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Open Archive Toulouse Archive Ouverte OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible This is an author’s version published in: https://oatao.univ-toulouse.fr/26232 Official URL : https://doi.org/10.5220/0007676201410148 To cite this version: Ait Brahim, Amal and Tighilt Ferhat, Rabah and Zurfluh, Gilles MDA process to extract the data model from a document-oriented NoSQL database. (2019) In: ICEIS 2019: 21st International Conference on Enterprise Information Systems, 3 May 2019 - 5 May 2019 (Heraklion, Greece). -
Database Systems Administrator FLSA: Exempt
CLOVIS UNIFIED SCHOOL DISTRICT POSITION DESCRIPTION Position: Database Systems Administrator FLSA: Exempt Department/Site: Technology Services Salary Grade: 127 Reports to/Evaluated by: Chief Technology Officer Salary Schedule: Classified Management SUMMARY Gathers requirements and provisions servers to meet the district’s need for database storage. Installs and configures SQL Server according to the specifications of outside software vendors and/or the development group. Designs and executes a security scheme to assure safety of confidential data. Implements and manages a backup and disaster recovery plan. Monitors the health and performance of database servers and database applications. Troubleshoots database application performance issues. Automates monitoring and maintenance tasks. Maintains service pack deployment and upgrades servers in consultation with the developer group and outside vendors. Deploys and schedules SQL Server Agent tasks. Implements and manages replication topologies. Designs and deploys datamarts under the supervision of the developer group. Deploys and manages cubes for SSAS implementations. DISTINGUISHING CAREER FEATURES The Database Systems Administrator is a senior level analyst position requiring specialized education and training in the field of study typically resulting in a degree. Advancement to this position would require competency in the design and administration of relational databases designated for business, enterprise, and student information. Advancement from this position is limited to supervisory management positions. ESSENTIAL DUTIES AND RESPONSIBILITIES Implements, maintains and administers all district supported versions of Microsoft SQL as well as other DBMS as needed. Responsible for database capacity planning and involvement in server capacity planning. Responsible for verification of backups and restoration of production and test databases. Designs, implements and maintains a disaster recovery plan for critical data resources. -
MDA Process to Extract the Data Model from Document-Oriented Nosql Database
MDA Process to Extract the Data Model from Document-oriented NoSQL Database Amal Ait Brahim, Rabah Tighilt Ferhat and Gilles Zurfluh Toulouse Institute of Computer Science Research (IRIT), Toulouse Capitole University, Toulouse, France Keywords: Big Data, NoSQL, Model Extraction, Schema Less, MDA, QVT. Abstract: In recent years, the need to use NoSQL systems to store and exploit big data has been steadily increasing. Most of these systems are characterized by the property "schema less" which means absence of the data model when creating a database. This property brings an undeniable flexibility by allowing the evolution of the model during the exploitation of the base. However, query expression requires a precise knowledge of the data model. In this article, we propose a process to automatically extract the physical model from a document- oriented NoSQL database. To do this, we use the Model Driven Architecture (MDA) that provides a formal framework for automatic model transformation. From a NoSQL database, we propose formal transformation rules with QVT to generate the physical model. An experimentation of the extraction process was performed on the case of a medical application. 1 INTRODUCTION however that it is absent in some systems such as Cassandra and Riak TS. The "schema less" property Recently, there has been an explosion of data offers undeniable flexibility by allowing the model to generated and accumulated by more and more evolve easily. For example, the addition of new numerous and diversified computing devices. attributes in an existing line is done without Databases thus constituted are designated by the modifying the other lines of the same type previously expression "Big Data" and are characterized by the stored; something that is not possible with relational so-called "3V" rule (Chen, 2014). -
What Is Nosql? the Only Thing That All Nosql Solutions Providers Generally Agree on Is That the Term “Nosql” Isn’T Perfect, but It Is Catchy
NoSQL GREG SYSADMINBURD Greg Burd is a Developer Choosing between databases used to boil down to examining the differences Advocate for Basho between the available commercial and open source relational databases . The term Technologies, makers of Riak. “database” had become synonymous with SQL, and for a while not much else came Before Basho, Greg spent close to being a viable solution for data storage . But recently there has been a shift nearly ten years as the product manager for in the database landscape . When considering options for data storage, there is a Berkeley DB at Sleepycat Software and then new game in town: NoSQL databases . In this article I’ll introduce this new cat- at Oracle. Previously, Greg worked for NeXT egory of databases, examine where they came from and what they are good for, and Computer, Sun Microsystems, and KnowNow. help you understand whether you, too, should be considering a NoSQL solution in Greg has long been an avid supporter of open place of, or in addition to, your RDBMS database . source software. [email protected] What Is NoSQL? The only thing that all NoSQL solutions providers generally agree on is that the term “NoSQL” isn’t perfect, but it is catchy . Most agree that the “no” stands for “not only”—an admission that the goal is not to reject SQL but, rather, to compensate for the technical limitations shared by the majority of relational database implemen- tations . In fact, NoSQL is more a rejection of a particular software and hardware architecture for databases than of any single technology, language, or product . -
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. -
Nosql Database Technology
NoSQL Database Technology Post-relational data management for interactive software systems NOSQL DATABASE TECHNOLOGY Table of Contents Summary 3 Interactive software has changed 4 Users – 4 Applications – 5 Infrastructure – 5 Application architecture has changed 6 Database architecture has not kept pace 7 Tactics to extend the useful scope of RDBMS technology 8 Sharding – 8 Denormalizing – 9 Distributed caching – 10 “NoSQL” database technologies 11 Mobile application data synchronization 13 Open source and commercial NoSQL database technologies 14 2 © 2011 COUCHBASE ALL RIGHTS RESERVED. WWW.COUCHBASE.COM NOSQL DATABASE TECHNOLOGY Summary Interactive software (software with which a person iteratively interacts in real time) has changed in fundamental ways over the last 35 years. The “online” systems of the 1970s have, through a series of intermediate transformations, evolved into today’s web and mobile appli- cations. These systems solve new problems for potentially vastly larger user populations, and they execute atop a computing infrastructure that has changed even more radically over the years. The architecture of these software systems has likewise transformed. A modern web ap- plication can support millions of concurrent users by spreading load across a collection of application servers behind a load balancer. Changes in application behavior can be rolled out incrementally without requiring application downtime by gradually replacing the software on individual servers. Adjustments to application capacity are easily made by changing the number of application servers. But database technology has not kept pace. Relational database technology, invented in the 1970s and still in widespread use today, was optimized for the applications, users and inf- rastructure of that era. -
SQL Vs Nosql: a Performance Comparison
SQL vs NoSQL: A Performance Comparison Ruihan Wang Zongyan Yang University of Rochester University of Rochester [email protected] [email protected] Abstract 2. ACID Properties and CAP Theorem We always hear some statements like ‘SQL is outdated’, 2.1. ACID Properties ‘This is the world of NoSQL’, ‘SQL is still used a lot by We need to refer the ACID properties[12]: most of companies.’ Which one is accurate? Has NoSQL completely replace SQL? Or is NoSQL just a hype? SQL Atomicity (Structured Query Language) is a standard query language A transaction is an atomic unit of processing; it should for relational database management system. The most popu- either be performed in its entirety or not performed at lar types of RDBMS(Relational Database Management Sys- all. tems) like Oracle, MySQL, SQL Server, uses SQL as their Consistency preservation standard database query language.[3] NoSQL means Not A transaction should be consistency preserving, meaning Only SQL, which is a collection of non-relational data stor- that if it is completely executed from beginning to end age systems. The important character of NoSQL is that it re- without interference from other transactions, it should laxes one or more of the ACID properties for a better perfor- take the database from one consistent state to another. mance in desired fields. Some of the NOSQL databases most Isolation companies using are Cassandra, CouchDB, Hadoop Hbase, A transaction should appear as though it is being exe- MongoDB. In this paper, we’ll outline the general differences cuted in iso- lation from other transactions, even though between the SQL and NoSQL, discuss if Relational Database many transactions are execut- ing concurrently. -
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. -
Applying the ETL Process to Blockchain Data. Prospect and Findings
information Article Applying the ETL Process to Blockchain Data. Prospect and Findings Roberta Galici 1, Laura Ordile 1, Michele Marchesi 1 , Andrea Pinna 2,* and Roberto Tonelli 1 1 Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy; [email protected] (R.G.); [email protected] (L.O.); [email protected] (M.M.); [email protected] (R.T.) 2 Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Piazza D’Armi, 09100 Cagliari, Italy * Correspondence: [email protected] Received: 7 March 2020; Accepted: 7 April 2020; Published: 10 April 2020 Abstract: We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. -
IBM Cloudant: Database As a Service Fundamentals
Front cover IBM Cloudant: Database as a Service Fundamentals Understand the basics of NoSQL document data stores Access and work with the Cloudant API Work programmatically with Cloudant data Christopher Bienko Marina Greenstein Stephen E Holt Richard T Phillips ibm.com/redbooks Redpaper Contents Notices . 5 Trademarks . 6 Preface . 7 Authors. 7 Now you can become a published author, too! . 8 Comments welcome. 8 Stay connected to IBM Redbooks . 9 Chapter 1. Survey of the database landscape . 1 1.1 The fundamentals and evolution of relational databases . 2 1.1.1 The relational model . 2 1.1.2 The CAP Theorem . 4 1.2 The NoSQL paradigm . 5 1.2.1 ACID versus BASE systems . 7 1.2.2 What is NoSQL? . 8 1.2.3 NoSQL database landscape . 9 1.2.4 JSON and schema-less model . 11 Chapter 2. Build more, grow more, and sleep more with IBM Cloudant . 13 2.1 Business value . 15 2.2 Solution overview . 16 2.3 Solution architecture . 18 2.4 Usage scenarios . 20 2.5 Intuitively interact with data using Cloudant Dashboard . 21 2.5.1 Editing JSON documents using Cloudant Dashboard . 22 2.5.2 Configuring access permissions and replication jobs within Cloudant Dashboard. 24 2.6 A continuum of services working together on cloud . 25 2.6.1 Provisioning an analytics warehouse with IBM dashDB . 26 2.6.2 Data refinement services on-premises. 30 2.6.3 Data refinement services on the cloud. 30 2.6.4 Hybrid clouds: Data refinement across on/off–premises. 31 Chapter 3. -
Top 5 Considerations When Evaluating Nosql Databases February 2015 Table of Contents
A MongoDB White Paper Top 5 Considerations When Evaluating NoSQL Databases February 2015 Table of Contents Introduction 1 Data Model 2 Document Model 2 Graph Model 2 Key-Value and Wide Column Models 2 Query Model 3 Document Database 3 Graph Database 3 Key Value and Wide Column Databases 3 Consistency Model 4 Consistent Systems 4 Eventually Consistent Systems 4 APIs 4 Idiomatic Drivers 5 Thrift or RESTful APIs 5 Pluggable Storage API 5 Commercial Support and Community Strength 5 Commercial Support 5 Community Strength 5 Conclusion 6 We Can Help 6 Introduction Relational databases have a long-standing position in most Development teams have a strong say in the technology organizations, and for good reason. Relational databases selection process. This community tends to find that the underpin legacy applications that meet current business relational data model is not well aligned with the needs of needs; they are supported by an extensive ecosystem of their applications. Consider: tools; and there is a large pool of labor qualified to • Developers are working with new data types — implement and maintain these systems. structured, semi-structured, unstructured and But companies are increasingly considering alternatives to polymorphic data — and massive volumes of it. legacy relational infrastructure. In some cases the • Long gone is the twelve-to-eighteen month waterfall motivation is technical — such as a need to scale or development cycle. Now small teams work in agile perform beyond the capabilities of their existing systems — sprints, iterating quickly and pushing code every week while in other cases companies are driven by the desire to or two, even every day.