the integration of database solutions within blockchain platforms is essential for ensuring the secure, efficient, and reliable management of blockchain data. The role of key-value stores, traditional databases, and specialized solutions such as LevelDB and RocksDB demonstrates the diverse and tailored approaches to addressing the unique requirements of blockchain data storage and retrieval. Practical considerations and best practices emphasize the importance of data privacy, scalability and performance optimization, laying the foundation for the future trends and innovations in decentralized database protocols, data sharding, Al and machine learning integration, and collaborative ecosystems. As blockchain technology continues to evolve, the seamless integration of database solutions will play a bold role in shaping the future of decentralized and distributed data management within blockchain ecosystems. The ongoing advancements in database technologies and their integration with blockchain platforms will contribute to the continued growth and innovation in the field of decentralized data management.
A database management system (or DBMS) is essentially nothing more than a computerized data-keeping system. Users of the system are given facilities to perform several kinds of operations on such a system for either manipulation of the data in the database or the management of the database structure itself.
This document provides an overview of NoSQL databases. It discusses that NoSQL databases are non-relational and do not follow the RDBMS principles. It describes some of the main types of NoSQL databases including document stores, key-value stores, column-oriented stores, and graph databases. It also discusses how NoSQL databases are designed for massive scalability and do not guarantee ACID properties, instead following a BASE model ofBasically Available, Soft state, and Eventually Consistent.
Comparative study of no sql document, column store databases and evaluation o...ijdms
In the last decade, rapid growth in mobile applications, web technologies, social media generating
unstructured data has led to the advent of various nosql data stores. Demands of web scale are in
increasing trend everyday and nosql databases are evolving to meet up with stern big data requirements.
The purpose of this paper is to explore nosql technologies and present a comparative study of document
and column store nosql databases such as cassandra, MongoDB and Hbase in various attributes of
relational and distributed database system principles. Detailed study and analysis of architecture and
internal working cassandra, Mongo DB and HBase is done theoretically and core concepts are depicted.
This paper also presents evaluation of cassandra for an industry specific use case and results are
published.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
CHAPTER 12 Integrating Non-Blockchain Apps with Ethereum EstelaJeffery653
CHAPTER 12 Integrating Non-Blockchain Apps with Ethereum 205
Chapter 12
Integrating Non-
Blockchain Apps
with Ethereum
Although you can build entirely blockchain-based applications, it is far more likely that your applications will be a combination of traditional and blockchain components. You learn in Chapter 3 that some use cases lend
themselves well to blockchain apps but others do not. In this book, we chose to
highlight one use case, supply chain, because blockchain offers clear advantages
over traditional methods. However, even a comprehensive supply chain applica-
tion will likely run partially as a traditional application and partially on the
blockchain.
Many emerging blockchain apps consist of core components that operate as smart
contracts and other components that operate as traditional applications that
interact with users and provide supporting functionality. This hybrid approach to
application development requires the capability to integrate the two different
development models. In other words, to develop hybrid applications that run par-
tially on the blockchain, you need to know how to design them to talk with each
other and operate seamlessly.
IN THIS CHAPTER
» Exploring differences between
blockchain and databases
» Identifying differences between
blockchain and traditional
applications
» Integrating traditional applications
with Ethereum
» Testing and deploying integrated
blockchain apps
206 PART 4 Testing and Deploying Ethereum Apps
Distributed application design and development isn’t new. In fact, some of the
difficulties with distributed applications led to the need for technologies like
blockchain. Remember that blockchain technology doesn’t solve all application
problems, but it does have its place. Now that you know how to develop dApps for
the Ethereum blockchain, in this chapter you learn how to integrate your smart
contracts with applications that do not include blockchain technology. The capa-
bility to integrate blockchain and non-blockchain applications makes it possible
to develop applications that use the right technology for a wide range of needs.
Comparing Blockchain and
Database Storage
In Chapter 2, you learn about some of the differences between storing data in a
blockchain and a database. Both technologies can store data, but clear differences
exist between the two. One of the first obstacles you might encounter when asked
to integrate blockchain with an existing application is determining what data you
should migrate to the blockchain.
Traditional applications store most of their data in a database. Databases provide
fast access to shared data. Blockchains can also provide access to shared data, but
they may not be as fast as a database. As you learn in Chapter 2, there are other
differences as well. It is important that you understand the relative strengths of
each data storage technique to make good design decisions for integrating block-
ch ...
The webinar was conducted by Bhuvan Gandhi and Vishwas Ganatra on 22-23 August, 2020. It was powered by Encode - The coding club of PDPU.
Bhuvan Gandhi - https://github.com/bmg02/database-workshop-encode
Vishwas Ganatra - https://github.com/vishwasganatra/Encode-database-workshop
The document provides an overview of the Databricks platform, which offers a unified environment for data engineering, analytics, and AI. It describes how Databricks addresses the complexity of managing data across siloed systems by providing a single "data lakehouse" platform where all data and analytics workloads can be run. Key features highlighted include Delta Lake for ACID transactions on data lakes, auto loader for streaming data ingestion, notebooks for interactive coding, and governance tools to securely share and catalog data and models.
This document discusses NoSQL databases and compares them to relational databases. It provides information on different types of NoSQL databases, including key-value stores, document databases, wide-column stores, and graph databases. The document outlines some use cases for each type and discusses concepts like eventual consistency, CAP theorem, and polyglot persistence. It also covers database architectures like replication and sharding that provide high availability and scalability.
A database management system (or DBMS) is essentially nothing more than a computerized data-keeping system. Users of the system are given facilities to perform several kinds of operations on such a system for either manipulation of the data in the database or the management of the database structure itself.
This document provides an overview of NoSQL databases. It discusses that NoSQL databases are non-relational and do not follow the RDBMS principles. It describes some of the main types of NoSQL databases including document stores, key-value stores, column-oriented stores, and graph databases. It also discusses how NoSQL databases are designed for massive scalability and do not guarantee ACID properties, instead following a BASE model ofBasically Available, Soft state, and Eventually Consistent.
Comparative study of no sql document, column store databases and evaluation o...ijdms
In the last decade, rapid growth in mobile applications, web technologies, social media generating
unstructured data has led to the advent of various nosql data stores. Demands of web scale are in
increasing trend everyday and nosql databases are evolving to meet up with stern big data requirements.
The purpose of this paper is to explore nosql technologies and present a comparative study of document
and column store nosql databases such as cassandra, MongoDB and Hbase in various attributes of
relational and distributed database system principles. Detailed study and analysis of architecture and
internal working cassandra, Mongo DB and HBase is done theoretically and core concepts are depicted.
This paper also presents evaluation of cassandra for an industry specific use case and results are
published.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
CHAPTER 12 Integrating Non-Blockchain Apps with Ethereum EstelaJeffery653
CHAPTER 12 Integrating Non-Blockchain Apps with Ethereum 205
Chapter 12
Integrating Non-
Blockchain Apps
with Ethereum
Although you can build entirely blockchain-based applications, it is far more likely that your applications will be a combination of traditional and blockchain components. You learn in Chapter 3 that some use cases lend
themselves well to blockchain apps but others do not. In this book, we chose to
highlight one use case, supply chain, because blockchain offers clear advantages
over traditional methods. However, even a comprehensive supply chain applica-
tion will likely run partially as a traditional application and partially on the
blockchain.
Many emerging blockchain apps consist of core components that operate as smart
contracts and other components that operate as traditional applications that
interact with users and provide supporting functionality. This hybrid approach to
application development requires the capability to integrate the two different
development models. In other words, to develop hybrid applications that run par-
tially on the blockchain, you need to know how to design them to talk with each
other and operate seamlessly.
IN THIS CHAPTER
» Exploring differences between
blockchain and databases
» Identifying differences between
blockchain and traditional
applications
» Integrating traditional applications
with Ethereum
» Testing and deploying integrated
blockchain apps
206 PART 4 Testing and Deploying Ethereum Apps
Distributed application design and development isn’t new. In fact, some of the
difficulties with distributed applications led to the need for technologies like
blockchain. Remember that blockchain technology doesn’t solve all application
problems, but it does have its place. Now that you know how to develop dApps for
the Ethereum blockchain, in this chapter you learn how to integrate your smart
contracts with applications that do not include blockchain technology. The capa-
bility to integrate blockchain and non-blockchain applications makes it possible
to develop applications that use the right technology for a wide range of needs.
Comparing Blockchain and
Database Storage
In Chapter 2, you learn about some of the differences between storing data in a
blockchain and a database. Both technologies can store data, but clear differences
exist between the two. One of the first obstacles you might encounter when asked
to integrate blockchain with an existing application is determining what data you
should migrate to the blockchain.
Traditional applications store most of their data in a database. Databases provide
fast access to shared data. Blockchains can also provide access to shared data, but
they may not be as fast as a database. As you learn in Chapter 2, there are other
differences as well. It is important that you understand the relative strengths of
each data storage technique to make good design decisions for integrating block-
ch ...
The webinar was conducted by Bhuvan Gandhi and Vishwas Ganatra on 22-23 August, 2020. It was powered by Encode - The coding club of PDPU.
Bhuvan Gandhi - https://github.com/bmg02/database-workshop-encode
Vishwas Ganatra - https://github.com/vishwasganatra/Encode-database-workshop
The document provides an overview of the Databricks platform, which offers a unified environment for data engineering, analytics, and AI. It describes how Databricks addresses the complexity of managing data across siloed systems by providing a single "data lakehouse" platform where all data and analytics workloads can be run. Key features highlighted include Delta Lake for ACID transactions on data lakes, auto loader for streaming data ingestion, notebooks for interactive coding, and governance tools to securely share and catalog data and models.
This document discusses NoSQL databases and compares them to relational databases. It provides information on different types of NoSQL databases, including key-value stores, document databases, wide-column stores, and graph databases. The document outlines some use cases for each type and discusses concepts like eventual consistency, CAP theorem, and polyglot persistence. It also covers database architectures like replication and sharding that provide high availability and scalability.
This document describes BigchainDB, a scalable blockchain database. BigchainDB combines the key benefits of distributed databases and blockchains, with an emphasis on scale. It is built on an existing distributed database to inherit high throughput, capacity, low latency, and querying abilities. BigchainDB also adds blockchain characteristics like decentralized control, immutability, and the ability to create and transfer digital assets. The goal is to provide a decentralized database at scale, filling a gap in existing blockchain technologies.
What Are The Best Databases for Web Applications In 2023.pdfLaura Miller
A database is used to store and manage structured & unstructured data in a system. Read the blog to know 2023's top seven databases for web applications.
NoSQL is a non-relational database designed for large-scale data storage needs. It has several key features: it is non-relational, schema-free, uses simple APIs, and is distributed. The four main types of NoSQL databases are key-value, column-oriented, document-oriented, and graph-based. Key advantages of NoSQL include scalability, flexibility in data structures, and ease of development. However, NoSQL sacrifices some consistency and lacks standardization compared to SQL databases.
decentralized cloud storage and blockchian.pdfqitchain.net
Decentralized Cloud Storage and Blockchain
What is Decentralization?
Decentralization is an ideology that advocates for a liberal style of administration in which no single authority has absolute power over all aspects of life. In a decentralized storage system, users may save their files without depending on large data hubs like the cloud.
Decentralization in data storage has gained recognition because of its user-friendly and trustable features like privacy and security. Decentralized data centers rely on a peer-to-peer network of users who each store small, encrypted chunks of the overall data. In this way, a reliable data storage and sharing system has been created that can be founded on blockchain or any other peer-to-peer network.
Decentralized cloud storage is a storage system in which data is saved on various computers or servers. It’s a decentralized P2P (peer-to-peer) cloud storage system.
Qitchain QTC is a Decentralized Cloud Storage technology that is both efficient and unique. The advantage of adopting such storage is that it can perform all of the tasks of a decentralized web, including security, privacy, no single point of failure, and cost-effectiveness.
The process of moving authority from a central government to a more decentralized and “liberal” framework is known as decentralization. Files are encrypted, fragmented, and disseminated throughout a global network rather than being kept in centralized data centers.
Decentralized storage is becoming more popular than centralized cloud storage for a variety of reasons.
Data breaches in centralized cloud storage have occurred in recent years, as have data outages, storage costs have increased, and most crucially, there is a lack of ownership. As a result, there was a compelling need to fix these concerns. These issues can be solvable via a decentralized storage system.
Read more here QITCHAIN: DECENTRALIZED SEARCH ENGINE
Decentralized Storage: How it Works
As in a decentralized storage system, the data is not stored on a single place but on multiple nodes. Client’s data is encrypted. It stores multiple copies of the same piece of data in separate locations. The users who have the encryption key are only allowed to access or read the file. This secure storage system motivates users to participate, host and hold servers in the system. Numerous small entities contribute to the network by generating storage space and computing power.
An extra blanket of protection and security is added via ‘Sharding’ process. Sharding refers to the process of distributing data over a network of nodes. Decentralized locations store the data and distribute it. Interlopers who try to break into these places will find encrypted data blocks. Furthermore, they will only be able to get a portion of the information, not the complete file. To sum it up, blockchain-based decentralized storage systems ensure high level of data security which no other storage system can provide.
CARBON NEUTRAL ENCRYPTED DIGITAL cu
The document discusses factors to consider when selecting a NoSQL database management system (DBMS). It provides an overview of different NoSQL database types, including document databases, key-value databases, column databases, and graph databases. For each type, popular open-source options are described, such as MongoDB for document databases, Redis for key-value, Cassandra for columnar, and Neo4j for graph databases. The document emphasizes choosing a NoSQL solution based on application needs and recommends commercial support for production systems.
Maginatics @ SDC 2013: Architecting An Enterprise Storage Platform Using Obje...Maginatics
How did Maginatics build a strongly consistent and secure distributed file system? Niraj Tolia, Chief Architect at Maginatics, gave this presentation on the design of MagFS at the Storage Developer Conference on September 16, 2013.
For more information about MagFS—The File System for the Cloud, visit maginatics.com or contact us directly at info@maginatics.com.
This document discusses NewSQL databases. It begins with an introduction that describes how enterprises need both reliable transaction processing and the ability to perform analytics on large datasets. This requires different database strategies that are often in conflict.
The document then provides details on NewSQL databases, including that they aim to overcome constraints of SQL and NoSQL databases. Key features of NewSQL databases are described, such as how they store data and provide security and support for big data. NewSQL databases are compared to SQL and NoSQL databases based on several parameters like ACID properties, storage, performance, consistency, and more. Overall, the document analyzes the rise of NewSQL databases as an attempt to achieve the benefits of both traditional SQL and No
Key aspects of big data storage and its architectureRahul Chaturvedi
This paper helps understand the tools and technologies related to a classic BigData setting. Someone who reads this paper, especially Enterprise Architects, will find it helpful in choosing several BigData database technologies in a Hadoop architecture.
The presentation begins with an overview of the growth of non-structured data and the benefits NoSQL products provide. It then provides an evaluation of the more popular NoSQL products on the market including MongoDB, Cassandra, Neo4J, and Redis. With NoSQL architectures becoming an increasingly appealing database management option for many organizations, this presentation will help you effectively evaluate the most popular NoSQL offerings and determine which one best meets your business needs.
Hyperledger Sawtooth Lake Intel's OSS Contribution to Enterprise BlockchainAltoros
Sawtooth Lake is an open source distributed ledger project within Hyperledger. It uses a blockchain architecture where each node holds a copy of the shared ledger and transactions are grouped into blocks and chained together cryptographically. Sawtooth Lake allows for modular transaction families that encapsulate business logic and smart contracts. The latest release focuses on improvements to transaction processing, including parallel execution and multi-language support.
This document discusses emerging trends in databases, including NoSQL databases and object-oriented databases. It provides information on the characteristics, categories, advantages, and disadvantages of NoSQL databases. It also compares relational databases to object-oriented databases and discusses object-relational mapping.
Prague data management meetup 2018-03-27Martin Bém
This document discusses different data types and data models. It begins by describing unstructured, semi-structured, and structured data. It then discusses relational and non-relational data models. The document notes that big data can include any of these data types and models. It provides an overview of Microsoft's data management and analytics platform and tools for working with structured, semi-structured, and unstructured data at varying scales. These include offerings like SQL Server, Azure SQL Database, Azure Data Lake Store, Azure Data Lake Analytics, HDInsight and Azure Data Warehouse.
5 Steps for Migrating Relational Databases to Next-Gen ArchitecturesNuoDB
The current “cloud first” revolution has exposed an ugly secret: Traditional databases simply cannot meet the high-scale, high availability, high customer expectation reality that business are facing. As more customers begin migrating mission-critical applications to database platforms that can inherently support next-generation flexibility and agility, it’s no wonder that the market for alternative database solutions is growing rapidly.
In this webinar, NayaTech CTO David Yahalom and NuoDB VP of Products Ariff Kassam discuss the primary motivators behind the growing adoption of next-generation, cloud-centric database technologies and the five steps to ensure such database migration projects are successful.
Topics include:
The main drivers behind the booming adoption of cloud-native, elastic, next-generation database technologies and the paradigm shift in the database technologies market.
The challenges for database migrations - from data movement and schema conversion to achieving feature parity with traditional commercial databases.
The five steps - from planning to execution - for a successful migration across different database platforms.
3.Implementation with NOSQL databases Document Databases (Mongodb).pptxRushikeshChikane2
this Chapter gives information about Document Based Database and Graph based Database. It gives their basic structures, Features,applications ,Limitations and use cases
Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in
The document provides an introduction to NoSQL databases, including key definitions and characteristics. It discusses that NoSQL databases are non-relational and do not follow RDBMS principles. It also summarizes different types of NoSQL databases like document stores, key-value stores, and column-oriented stores. Examples of popular databases for each type are also provided.
This document summarizes key components of Microsoft Azure's data platform, including SQL Database, NoSQL options like Azure Tables, Blob Storage, and Azure Files. It provides an overview of each service, how they work, common use cases, and demos of creating resources and accessing data. The document is aimed at helping readers understand Azure's database and data storage options for building cloud applications.
Web databases refer to databases that are accessed or manipulated via the world wide web. They are used to store information for websites, web apps, and mobile apps. There are two main categories of web databases: relational databases like MySQL use schemas and SQL, while non-relational databases like MongoDB are more flexible and don't require predefined schemas. Relational databases are better for applications needing complex queries, while non-relational databases are more scalable and flexible for handling large, unstructured data.
This document analyzes the performance of MongoDB and HBase databases. It describes the architectures and key characteristics of each database, including MongoDB's document model, auto-sharding, and replication features. It also covers HBase's use of HDFS for storage and Zookeeper for coordination. The document examines the security features of each database, such as authentication, authorization, and encryption. Finally, it discusses findings from literature that NoSQL databases sacrifice ACID properties for scalability and performance.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
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This document describes BigchainDB, a scalable blockchain database. BigchainDB combines the key benefits of distributed databases and blockchains, with an emphasis on scale. It is built on an existing distributed database to inherit high throughput, capacity, low latency, and querying abilities. BigchainDB also adds blockchain characteristics like decentralized control, immutability, and the ability to create and transfer digital assets. The goal is to provide a decentralized database at scale, filling a gap in existing blockchain technologies.
What Are The Best Databases for Web Applications In 2023.pdfLaura Miller
A database is used to store and manage structured & unstructured data in a system. Read the blog to know 2023's top seven databases for web applications.
NoSQL is a non-relational database designed for large-scale data storage needs. It has several key features: it is non-relational, schema-free, uses simple APIs, and is distributed. The four main types of NoSQL databases are key-value, column-oriented, document-oriented, and graph-based. Key advantages of NoSQL include scalability, flexibility in data structures, and ease of development. However, NoSQL sacrifices some consistency and lacks standardization compared to SQL databases.
decentralized cloud storage and blockchian.pdfqitchain.net
Decentralized Cloud Storage and Blockchain
What is Decentralization?
Decentralization is an ideology that advocates for a liberal style of administration in which no single authority has absolute power over all aspects of life. In a decentralized storage system, users may save their files without depending on large data hubs like the cloud.
Decentralization in data storage has gained recognition because of its user-friendly and trustable features like privacy and security. Decentralized data centers rely on a peer-to-peer network of users who each store small, encrypted chunks of the overall data. In this way, a reliable data storage and sharing system has been created that can be founded on blockchain or any other peer-to-peer network.
Decentralized cloud storage is a storage system in which data is saved on various computers or servers. It’s a decentralized P2P (peer-to-peer) cloud storage system.
Qitchain QTC is a Decentralized Cloud Storage technology that is both efficient and unique. The advantage of adopting such storage is that it can perform all of the tasks of a decentralized web, including security, privacy, no single point of failure, and cost-effectiveness.
The process of moving authority from a central government to a more decentralized and “liberal” framework is known as decentralization. Files are encrypted, fragmented, and disseminated throughout a global network rather than being kept in centralized data centers.
Decentralized storage is becoming more popular than centralized cloud storage for a variety of reasons.
Data breaches in centralized cloud storage have occurred in recent years, as have data outages, storage costs have increased, and most crucially, there is a lack of ownership. As a result, there was a compelling need to fix these concerns. These issues can be solvable via a decentralized storage system.
Read more here QITCHAIN: DECENTRALIZED SEARCH ENGINE
Decentralized Storage: How it Works
As in a decentralized storage system, the data is not stored on a single place but on multiple nodes. Client’s data is encrypted. It stores multiple copies of the same piece of data in separate locations. The users who have the encryption key are only allowed to access or read the file. This secure storage system motivates users to participate, host and hold servers in the system. Numerous small entities contribute to the network by generating storage space and computing power.
An extra blanket of protection and security is added via ‘Sharding’ process. Sharding refers to the process of distributing data over a network of nodes. Decentralized locations store the data and distribute it. Interlopers who try to break into these places will find encrypted data blocks. Furthermore, they will only be able to get a portion of the information, not the complete file. To sum it up, blockchain-based decentralized storage systems ensure high level of data security which no other storage system can provide.
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The document discusses factors to consider when selecting a NoSQL database management system (DBMS). It provides an overview of different NoSQL database types, including document databases, key-value databases, column databases, and graph databases. For each type, popular open-source options are described, such as MongoDB for document databases, Redis for key-value, Cassandra for columnar, and Neo4j for graph databases. The document emphasizes choosing a NoSQL solution based on application needs and recommends commercial support for production systems.
Maginatics @ SDC 2013: Architecting An Enterprise Storage Platform Using Obje...Maginatics
How did Maginatics build a strongly consistent and secure distributed file system? Niraj Tolia, Chief Architect at Maginatics, gave this presentation on the design of MagFS at the Storage Developer Conference on September 16, 2013.
For more information about MagFS—The File System for the Cloud, visit maginatics.com or contact us directly at info@maginatics.com.
This document discusses NewSQL databases. It begins with an introduction that describes how enterprises need both reliable transaction processing and the ability to perform analytics on large datasets. This requires different database strategies that are often in conflict.
The document then provides details on NewSQL databases, including that they aim to overcome constraints of SQL and NoSQL databases. Key features of NewSQL databases are described, such as how they store data and provide security and support for big data. NewSQL databases are compared to SQL and NoSQL databases based on several parameters like ACID properties, storage, performance, consistency, and more. Overall, the document analyzes the rise of NewSQL databases as an attempt to achieve the benefits of both traditional SQL and No
Key aspects of big data storage and its architectureRahul Chaturvedi
This paper helps understand the tools and technologies related to a classic BigData setting. Someone who reads this paper, especially Enterprise Architects, will find it helpful in choosing several BigData database technologies in a Hadoop architecture.
The presentation begins with an overview of the growth of non-structured data and the benefits NoSQL products provide. It then provides an evaluation of the more popular NoSQL products on the market including MongoDB, Cassandra, Neo4J, and Redis. With NoSQL architectures becoming an increasingly appealing database management option for many organizations, this presentation will help you effectively evaluate the most popular NoSQL offerings and determine which one best meets your business needs.
Hyperledger Sawtooth Lake Intel's OSS Contribution to Enterprise BlockchainAltoros
Sawtooth Lake is an open source distributed ledger project within Hyperledger. It uses a blockchain architecture where each node holds a copy of the shared ledger and transactions are grouped into blocks and chained together cryptographically. Sawtooth Lake allows for modular transaction families that encapsulate business logic and smart contracts. The latest release focuses on improvements to transaction processing, including parallel execution and multi-language support.
This document discusses emerging trends in databases, including NoSQL databases and object-oriented databases. It provides information on the characteristics, categories, advantages, and disadvantages of NoSQL databases. It also compares relational databases to object-oriented databases and discusses object-relational mapping.
Prague data management meetup 2018-03-27Martin Bém
This document discusses different data types and data models. It begins by describing unstructured, semi-structured, and structured data. It then discusses relational and non-relational data models. The document notes that big data can include any of these data types and models. It provides an overview of Microsoft's data management and analytics platform and tools for working with structured, semi-structured, and unstructured data at varying scales. These include offerings like SQL Server, Azure SQL Database, Azure Data Lake Store, Azure Data Lake Analytics, HDInsight and Azure Data Warehouse.
5 Steps for Migrating Relational Databases to Next-Gen ArchitecturesNuoDB
The current “cloud first” revolution has exposed an ugly secret: Traditional databases simply cannot meet the high-scale, high availability, high customer expectation reality that business are facing. As more customers begin migrating mission-critical applications to database platforms that can inherently support next-generation flexibility and agility, it’s no wonder that the market for alternative database solutions is growing rapidly.
In this webinar, NayaTech CTO David Yahalom and NuoDB VP of Products Ariff Kassam discuss the primary motivators behind the growing adoption of next-generation, cloud-centric database technologies and the five steps to ensure such database migration projects are successful.
Topics include:
The main drivers behind the booming adoption of cloud-native, elastic, next-generation database technologies and the paradigm shift in the database technologies market.
The challenges for database migrations - from data movement and schema conversion to achieving feature parity with traditional commercial databases.
The five steps - from planning to execution - for a successful migration across different database platforms.
3.Implementation with NOSQL databases Document Databases (Mongodb).pptxRushikeshChikane2
this Chapter gives information about Document Based Database and Graph based Database. It gives their basic structures, Features,applications ,Limitations and use cases
Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in
The document provides an introduction to NoSQL databases, including key definitions and characteristics. It discusses that NoSQL databases are non-relational and do not follow RDBMS principles. It also summarizes different types of NoSQL databases like document stores, key-value stores, and column-oriented stores. Examples of popular databases for each type are also provided.
This document summarizes key components of Microsoft Azure's data platform, including SQL Database, NoSQL options like Azure Tables, Blob Storage, and Azure Files. It provides an overview of each service, how they work, common use cases, and demos of creating resources and accessing data. The document is aimed at helping readers understand Azure's database and data storage options for building cloud applications.
Web databases refer to databases that are accessed or manipulated via the world wide web. They are used to store information for websites, web apps, and mobile apps. There are two main categories of web databases: relational databases like MySQL use schemas and SQL, while non-relational databases like MongoDB are more flexible and don't require predefined schemas. Relational databases are better for applications needing complex queries, while non-relational databases are more scalable and flexible for handling large, unstructured data.
This document analyzes the performance of MongoDB and HBase databases. It describes the architectures and key characteristics of each database, including MongoDB's document model, auto-sharding, and replication features. It also covers HBase's use of HDFS for storage and Zookeeper for coordination. The document examines the security features of each database, such as authentication, authorization, and encryption. Finally, it discusses findings from literature that NoSQL databases sacrifice ACID properties for scalability and performance.
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This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
4. ➢ Blockchain: cryptographically-secured transactional machine
➢ Cryptographically signed transaction modifies the blockchain state
➢ Databases: components that store the state written in the shared
blockchain ledger
Role of Databases in Blockchain
5. ➢ Blockchain State
○ Global truth about the overall information
➢ Blockchain components
○ Consensus Component
○ Network Component
Blockchain Components and Global State
6. Immutable Data Storage
Blockchain databases ensure the immutability of
data, preventing unauthorized modifications and
maintaining a secure record of transactions and
information. The database solutions used within
blockchain platforms are designed to enforce the
integrity and permanence of the stored data,
aligning with the core principles of blockchain
technology.
Privacy and Compliance in Blockchain Databases
02
01
Consensus Algorithms
The choice of database solutions within blockchain
platforms aligns with the consensus mechanisms
employed, such as proof of work, proof of stake, or
other consensus models. The database solutions
support the consensus algorithms by providing the
necessary data storage and retrieval capabilities to
facilitate the validation and recording of
transactions according to the consensus rules.
8. Databases within blockchain platforms play a crucial
role in storing the state written in the shared
blockchain ledger, ensuring the integrity and security
of the data. This storage is fundamental to maintaining
an accurate and tamper-proof record of transactions
and information within the blockchain network.
Role of Databases in Blockchain
Storage of Shared Ledger
Many platforms utilize key-value stores such as
LevelDB or RocksDB, which offer write-optimized
storage solutions for fast lookups and efficient data
retrieval. These key-value stores are designed to
handle the specific requirements of blockchain data
storage, providing the necessary performance and
reliability for managing the blockchain ledger.
Key-Value Stores
9. ❖ Merges blockchain and database properties
❖ Combine the best of the two technologies
❖ Nodes Local MongoDB database
Background of Databases in Blockchain
BigchainDB
❖ Decentralized blockchain features
❖ Optimized query processing
❖ Distributed approach
❖ Only a subset of changes by transactions
within a given block are stored into
distributed hash tables
ChainSQL
10. ❖ Storage engine
❖ Data provenance
❖ Implements necessary features
Data Provenance OR Additional File Systems
Forkbase
❖ Additional key-value stores or file systems
❖ Additional development cost
❖ Performance overhead
Ethereum
11. 1 2 3
Role of Key-Value
Stores
Key-value stores like LevelDB
and RocksDB are prevalent
within blockchain platforms due
to their ability to perform fast
lookups and efficient data
retrieval, essential for
blockchain operations. These
database solutions are
optimized to handle the unique
characteristics of blockchain
data, including the high volume
of transactions and the
distributed nature of the ledger.
Integration of
Traditional Databases
Traditional databases, including
SQL and NoSQL solutions, are
also integrated into blockchain
platforms to support diverse
data storage and retrieval
needs. The integration of
traditional databases enables
blockchain developers to
leverage established data
management technologies
while addressing the specific
requirements of blockchain
applications.
Scalability and
Performance
Database solutions for
blockchain prioritize scalability
and performance to
accommodate the growing
volume of transactions and
data within the network. These
solutions are engineered to
handle the increasing demands
on data storage and retrieval
while maintaining the efficiency
and responsiveness of the
blockchain platform.
Database Solutions for Blockchain
12. These are open to anyone and
are not controlled by a central
authority, providing transparency
and accessibility to all
participants in the network.
Public blockchains leverage
database solutions to store and
manage the shared ledger,
enabling decentralized and
permissionless access to the
recorded data and transactions.
Types of Blockchain Databases
Public Blockchains
In contrast, private blockchains
are permissioned and restrict
access to authorized entities,
ensuring privacy and control over
the network. Database solutions
for private blockchains focus on
maintaining data confidentiality
and access control, catering to
the specific governance and
security requirements of closed
blockchain ecosystems.
Private Blockchains
Some platforms leverage hybrid
blockchains, combining elements
of both public and private
blockchains to cater to diverse
use cases and requirements.
Database solutions within hybrid
blockchains are designed to
accommodate the varying levels
of transparency, privacy, and
accessibility needed for different
aspects of the blockchain
network.
Hybrid Blockchains
15. Faster lookups are a key factory
Some platforms use multiple option
The choice depends on the specific requirements, such as scalability, performance,
security, and data structure.
13 out of 20 blockchain platforms use key-value stores
Overall Result
17. Column Family Databases
Document Stores
Key-value Stores
Types of Databases Used in Blockchain
Objects and Blob Stores
Tabular Databases
Graph Databases
18. Blockchain data is stored
as ordered key-value pairs
of string sequences (byte
arrays in the background).
Database states are stored
as read-only snapshots,
which can be referenced
when needed.
The read performance is
improved by automatically
compressing data before
persistently storing it to the
disk. Also, caching is used
to avoid decompressing
data for each query.
LevelDB
An open-source on-disk
key-value store. The core
storage architecture of
LevelDB is a log-structured
merge tree (LSM), which is a
write-optimized B-tree
variant. It is optimized for
large sequential writes as
opposed to small random
writes.
★ It's used in various applications, including Google Chrome's IndexedDB, Bitcoin Core, go-ethereum.
19. An LSM tree is a data structure with performance
characteristics that make it attractive for providing
indexed access to files with high insert volume,
such as transactional log data. LSM trees maintain
data in two or more separate structures, each of
which is optimized for its respective underlying
storage medium. Data is synchronized between the
two structures efficiently, in batches.
log-structured merge (LSM)
A B-tree is a self-balancing tree data structure that
maintains sorted data and allows for efficient
searches, sequential access, insertions, and
deletions in logarithmic time. The B-tree
generalizes the binary search tree, allowing for
nodes with more than two children.
B-tree
20. LevelDB
LevelDB stores keys and values in arbitrary byte arrays, and data is sorted by key. This
means you can store any type of data (not just strings) as long as it can be represented
as a byte array.
LevelDB has three basic operations: Get, Put, and Delete. Get retrieves a value given a
key, Put writes a value into a key (creating the key if it doesn't exist), and Delete removes
the key and it's value.
Data Storage
Basic
Operations
Batching
Writes and
Iteration
LevelDB supports batching writes, which means you can write multiple key-value pairs at
once. It also supports forward and backward iteration over the keys and values.
21. LevelDB
LevelDB supports compression of the data via Google's Snappy compression library. This
helps reduce the storage space required for the data.
LevelDB is a NoSQL database, which means it does not have a relational data model and
it does not support SQL queries. It also does not support indexes.
Compression
NoSQL
Database
Usage as a
Library
Applications use LevelDB as a library, as it does not provide a server or command-line
interface
22. LevelDB serves as the storage
engine for Ethereum, providing
efficient data management
capabilities for the Ethereum
blockchain network. The
integration of LevelDB within the
Ethereum platform supports the
reliable storage and retrieval of
blockchain data, contributing to
the operational integrity and
performance of the Ethereum
blockchain.
Ethereum Blockchain and LevelDB
Storage Engine for Ethereum
It supports the storage of smart
contracts, transaction data, and
state information, contributing to
the operational integrity of the
Ethereum platform. The support
for smart contracts and
transaction data storage within
LevelDB enhances the
functionality and reliability of
Ethereum's blockchain
applications, ensuring the secure
and efficient execution of smart
contract operations.
Support for Smart Contracts
The integration of LevelDB
addresses scalability challenges,
ensuring the seamless storage
and retrieval of blockchain data
within the Ethereum ecosystem.
The scalability features of
LevelDB support the growing
demands for data storage and
access within the Ethereum
blockchain, providing a robust
and adaptable solution for
managing the expanding volume
of transactions and state
information.
Scalability Challenges
23. RocksDB uses the
column-oriented approach
in persistent storage.
Specifically, RocksDB uses
the concept of column
families to partition the
database logically.
It was developed by
Facebook to meet the
high-performance
requirements of key-value
stores in the era of flash
storage. tts primary goal is
to fully use the fast access
speed provided by
fashstorage, and adapt to
different workloads.
RocksDB
RocksDB is an open-source,
embeddable, persistent
key-value store for fast
storage. Like LevelDB,
RocksDB also stores keys
and values in arbitrary byte
arrays, and data is sorted
byte-wise by key or by
providing a custom
comparator.
24. RocksDB
RocksDB organizes all data in sorted order and the common operations are Get (key), Put
(key), Delete (key) and Scan (key).
RocksDB provides basic operations such as opening and closing a database, reading and
writing to more advanced operations such as merging and compaction filters
Data Storage
Basic
Operations
High
Performance
RocksDB uses a log-structured database engine, written entirely in C++, for maximum
performance. Keys and values are just arbitrarily-sized byte streams.
25. RocksDB
RocksDB is optimized for fast, low latency storage such as flash drives and high-speed
disk drives. RocksDB exploits the full potential of high read/write rates offered by flash or
RAM.
RocksDB is adaptable to different workloads. From database storage engines such as
MyRocks to application data caching to embedded workloads, RocksDB can be used for
a variety of data needs.
Optimized for
Fast Storage
Adaptable
26. PostgreSQL
● Requires upfront schema definition, which can be difficult for blockchain's dynamic
nature.
● Data type selection for large hash values can be inefficient (e.g., INTEGER vs.
BIGINT).
● Schema design impacts query performance significantly. (the mismatch between
32- and 64-bit values)
● Backward iteration not natively supported.
● ACID (Atomicity, Consistency, Isolation, Durability) compliance ensures data
integrity and provenance.
● Data recovery and availability through replication.
Fixed schema
challenges
Benefits
27. PostgreSQL
● Careful schema design is crucial for optimal performance in PostgreSQL for blockchain data.
● Must consider alternative data types for hash values to optimize storage.
● Leverage replication for data protection and availability.
● Potential performance implications of schema design choices, especially for query execution.
● Explore workarounds for backward iteration if needed.
29. Growing trend of
tokenization,
representing
real-world assets on
the blockchain for
increased liquidity.
Increased use of smart
contracts for
automation and
efficiency in various
industries.
Integration of AI and
machine learning with
blockchain for
advanced data
analytics and insights.
Future Trends in Blockchain
Interoperability will be
a key focus, allowing
different blockchains
to work together
seamlessly.
3
2
1 4
30. Conclusion and Discussion
In conclusion, the integration of database solutions within blockchain platforms is
essential for ensuring the secure, efficient, and reliable management of
blockchain data. The role of key-value stores, traditional databases, and
specialized solutions such as LevelDB and RocksDB demonstrates the diverse
and tailored approaches to addressing the unique requirements of blockchain
data storage and retrieval. Practical considerations and best practices emphasize
the importance of data privacy, scalability and performance optimization, laying
the foundation for the future trends and innovations in decentralized database
protocols, data sharding, Al and machine learning integration, and collaborative
ecosystems. As blockchain technology continues to evolve, the seamless
integration of database solutions will play a bold role in shaping the future of
decentralized and distributed data management within blockchain ecosystems.
The ongoing advancements in database technologies and their integration with
blockchain platforms will contribute to the continued growth and innovation in
the field of decentralized data management.
31. Future advancements in
blockchain databases are
likely to focus on enhancing
scalability and data privacy.
The choice of database
solution depends on the
specific requirements of
the blockchain application,
such as scalability,
performance, security, and
data structure.
Conclusion and Discussion
Database solutions are a
critical component of
blockchain platforms,
providing the necessary
infrastructure for data
management and storage.