Weaving the ILP Fabric into Bigchain DBInterledger
Dimitri De Jonghe presents on how Bigchain DB can use Interledger to connect disparate systems. Presented at the Interleder Workshop in London on 7/6/2016. Full presentation here: https://interledger.org/presentations/2016-07-06%20-%20ILP%20Workshop%20London%202016.pdf
Weaving the ILP Fabric into Bigchain DBInterledger
Dimitri De Jonghe presents on how Bigchain DB can use Interledger to connect disparate systems. Presented at the Interleder Workshop in London on 7/6/2016. Full presentation here: https://interledger.org/presentations/2016-07-06%20-%20ILP%20Workshop%20London%202016.pdf
An introduction to Blockchain and covering :
-Blockchain vs cryptocurrency
-Bitcoin vs Ethereum
-Real life and industrial examples
-Business example
-Benefits & challenges
If you are new to Blockchain, this intro will guide you through the main concepts, use cases and technologies behind it. Blockchain is a revolution that goes beyond Bitcoins. It will involve the relationships between normal people and governments or established power, other than the way most of the the applications we use today works.
Consider this an effective Blockchain guide for newcomers. These slides have been developed and used in an Open Lesson at the Geeks Academy.
A brief introduction to Blockchain and the underlying technology of distributed computing, challenges and future scope.
Copyrights belong to the respective owners, intention is purely for informational/educational purpose
I would like to thank various blogs, technical tutorials, books, videos to help me understand the basics and collate this presentaion
During this presentation, we will cover a brief introduction into Blockchain technology, historic use cases & emerging trends for Blockchain technology. We will also touch on what to expect from Blockchain technology in 2019. It is important to understand the progress that is being achieved every day with every single step we take towards real use cases for Blockchain projects. 2019 might be the first year where the Blockchain starts to become a central part in people’s lives and in some industries.
Main points covered:
• Conduct a brief introduction to Blockchain technology;
• Discuss both historic use cases and emerging trends for Blockchain technology;
• What to expect from Blockchain technology in 2019
Presenter:
Our presenter for this webinar is Kenneth Kimbel, a Cybersecurity professional with over five years of overall experience providing diverse technology services in client-facing roles. Recent Master’s in Cybersecurity Risk Management as well as a JD with a Cybersecurity Law focus. Currently, Kenneth is a data privacy and Cybersecurity Advisory Consultant with Deloitte. He is also knowledgeable on both current technical and legal issues in security.
Date: March 27th, 2019
Recorded webinar: https://youtu.be/fLjVgj6MAPY
Blockchain Beyond Finance - Cronos Groep - Jan 17, 2017BigchainDB
Towards the internet of value & trust.
"To develop shared global compute infrastructure,
we must first understand the status quo of infrastructure,
...and how to change it accordingly."
Dimitri De Jonghe, lead developer of BigchainDB talking about blockchain technology beyond the financial sector.
Why Blockchain Matters to Big Data - Big Data London Meetup - Nov 3, 2016BigchainDB
Why does blockchain matter to Big Data?
Bruce Pon, CEO and Co-Founder of BigchainDB talks about how blockchain and big data work together.
Follow BigchainDB on LinkedIn, download the whitepaper or sign up with at the IPDB Foundation to get access to a first test network build with BigchainDB to build your own blockchain application.
Intro to Blockchain - And, by the way, what the heck is proof-of-work?Jim Flynn
An overview of bitcoin and the blockchain with a more in-depth description of proof of work (POW). Conde samples used to demonstrate the concepts behind POW are available at http://jamespflynn.com.
14 Jan17- Nullmeets -Blockchain concept decoded by Ninad SarangNinad Sarang
Introduction to Blockchain and Bitcoin technologies
Things we will cover,
* What is TRANSACTION ?
* BlockChain !!!……Never heard what is that??
* The BTC Aka BitCoins
* Who discovered?
* How it works?
* Advantages & Disadvantages
* Applications
Blockchain Essentials for Enterprise ArchitectsGokul Alex
My session on Blockchain : Protocols, Platforms, Principles and Paradigms presented in the Benagluru Chamber of Industries and Commerce #BCIC Talk Series held at VMware Software India in collaboration with WomenWhoCode. This presentation is a compilation of essential concepts about Bitcoin, Ethereum, IPFS, Hyperledger, R3 Corda.
Grokking TechTalk #17: Introduction to blockchainGrokking VN
Speaker: Do The Luan - CARDADO labo
Bio: I work currently for CARDADOlabo, a Japanese Fintech startup. I'm obsessed by Ethereum and I have had a strong passion of research. I hold B.S from University of Science of HCM city and a M.S of computer science from La Rochelle University. I was a lecturer for 3 years at the University of Information Technology.
Description:
In this talk, Luan will share with us a high-level technical introduction about Blockchain, Bitcoin and Eutherium.
- What is blockchain and how is it related to bitcoin?
- What is Ethereum, the second-generation of blockchain
By allowing digital information to be distributed but not copied, blockchain technology created the backbone of a new type of internet. Originally devised for the digital currency, Bitcoin, the tech community is now finding other potential uses for the Blockchain technology.
Ethereum, 2nd generation blockchain technology, is an open source blockchain project that was built specifically to realize the coding of simple contracts on distributed ledgers. Still in its early stages, Ethereum has the potential to leverage the usefulness of blockchain on a truly worldchanging scale.
MongoDB Europe 2016 - Distributed Ledgers, Blockchain + MongoDBMongoDB
Blockchain is a decentralized, distributed ledger in which users can validate transactions without need for an intermediary 3rd party. As a publicly available, and secure ledger it could replace traditional commercial banking as we understand it. Institutional banks are already integrating this technology as they implement their own private side-chains. As a distributed ledger, blockchain can be used for purposes outside finance, including voting systems and identity registration. Yet, Blockchain is still only one component of a full application architecture. Practical use of use of blockchain will require integration with Spark & Hadoop for analytics capabilities and MongoDB for service to real-time application loads. This talk will describe and demystify blockchain and provide integrations Spark and MongoDB to produce truly performant, innovative and robust applications.
Rather than trying to scale up blockchain technology, BigchainDB starts with a big data distributed database and then adds blockchain characteristics - decentralized control, immutability and the transfer of digital assets.
An introduction to Blockchain and covering :
-Blockchain vs cryptocurrency
-Bitcoin vs Ethereum
-Real life and industrial examples
-Business example
-Benefits & challenges
If you are new to Blockchain, this intro will guide you through the main concepts, use cases and technologies behind it. Blockchain is a revolution that goes beyond Bitcoins. It will involve the relationships between normal people and governments or established power, other than the way most of the the applications we use today works.
Consider this an effective Blockchain guide for newcomers. These slides have been developed and used in an Open Lesson at the Geeks Academy.
A brief introduction to Blockchain and the underlying technology of distributed computing, challenges and future scope.
Copyrights belong to the respective owners, intention is purely for informational/educational purpose
I would like to thank various blogs, technical tutorials, books, videos to help me understand the basics and collate this presentaion
During this presentation, we will cover a brief introduction into Blockchain technology, historic use cases & emerging trends for Blockchain technology. We will also touch on what to expect from Blockchain technology in 2019. It is important to understand the progress that is being achieved every day with every single step we take towards real use cases for Blockchain projects. 2019 might be the first year where the Blockchain starts to become a central part in people’s lives and in some industries.
Main points covered:
• Conduct a brief introduction to Blockchain technology;
• Discuss both historic use cases and emerging trends for Blockchain technology;
• What to expect from Blockchain technology in 2019
Presenter:
Our presenter for this webinar is Kenneth Kimbel, a Cybersecurity professional with over five years of overall experience providing diverse technology services in client-facing roles. Recent Master’s in Cybersecurity Risk Management as well as a JD with a Cybersecurity Law focus. Currently, Kenneth is a data privacy and Cybersecurity Advisory Consultant with Deloitte. He is also knowledgeable on both current technical and legal issues in security.
Date: March 27th, 2019
Recorded webinar: https://youtu.be/fLjVgj6MAPY
Blockchain Beyond Finance - Cronos Groep - Jan 17, 2017BigchainDB
Towards the internet of value & trust.
"To develop shared global compute infrastructure,
we must first understand the status quo of infrastructure,
...and how to change it accordingly."
Dimitri De Jonghe, lead developer of BigchainDB talking about blockchain technology beyond the financial sector.
Why Blockchain Matters to Big Data - Big Data London Meetup - Nov 3, 2016BigchainDB
Why does blockchain matter to Big Data?
Bruce Pon, CEO and Co-Founder of BigchainDB talks about how blockchain and big data work together.
Follow BigchainDB on LinkedIn, download the whitepaper or sign up with at the IPDB Foundation to get access to a first test network build with BigchainDB to build your own blockchain application.
Intro to Blockchain - And, by the way, what the heck is proof-of-work?Jim Flynn
An overview of bitcoin and the blockchain with a more in-depth description of proof of work (POW). Conde samples used to demonstrate the concepts behind POW are available at http://jamespflynn.com.
14 Jan17- Nullmeets -Blockchain concept decoded by Ninad SarangNinad Sarang
Introduction to Blockchain and Bitcoin technologies
Things we will cover,
* What is TRANSACTION ?
* BlockChain !!!……Never heard what is that??
* The BTC Aka BitCoins
* Who discovered?
* How it works?
* Advantages & Disadvantages
* Applications
Blockchain Essentials for Enterprise ArchitectsGokul Alex
My session on Blockchain : Protocols, Platforms, Principles and Paradigms presented in the Benagluru Chamber of Industries and Commerce #BCIC Talk Series held at VMware Software India in collaboration with WomenWhoCode. This presentation is a compilation of essential concepts about Bitcoin, Ethereum, IPFS, Hyperledger, R3 Corda.
Grokking TechTalk #17: Introduction to blockchainGrokking VN
Speaker: Do The Luan - CARDADO labo
Bio: I work currently for CARDADOlabo, a Japanese Fintech startup. I'm obsessed by Ethereum and I have had a strong passion of research. I hold B.S from University of Science of HCM city and a M.S of computer science from La Rochelle University. I was a lecturer for 3 years at the University of Information Technology.
Description:
In this talk, Luan will share with us a high-level technical introduction about Blockchain, Bitcoin and Eutherium.
- What is blockchain and how is it related to bitcoin?
- What is Ethereum, the second-generation of blockchain
By allowing digital information to be distributed but not copied, blockchain technology created the backbone of a new type of internet. Originally devised for the digital currency, Bitcoin, the tech community is now finding other potential uses for the Blockchain technology.
Ethereum, 2nd generation blockchain technology, is an open source blockchain project that was built specifically to realize the coding of simple contracts on distributed ledgers. Still in its early stages, Ethereum has the potential to leverage the usefulness of blockchain on a truly worldchanging scale.
MongoDB Europe 2016 - Distributed Ledgers, Blockchain + MongoDBMongoDB
Blockchain is a decentralized, distributed ledger in which users can validate transactions without need for an intermediary 3rd party. As a publicly available, and secure ledger it could replace traditional commercial banking as we understand it. Institutional banks are already integrating this technology as they implement their own private side-chains. As a distributed ledger, blockchain can be used for purposes outside finance, including voting systems and identity registration. Yet, Blockchain is still only one component of a full application architecture. Practical use of use of blockchain will require integration with Spark & Hadoop for analytics capabilities and MongoDB for service to real-time application loads. This talk will describe and demystify blockchain and provide integrations Spark and MongoDB to produce truly performant, innovative and robust applications.
Rather than trying to scale up blockchain technology, BigchainDB starts with a big data distributed database and then adds blockchain characteristics - decentralized control, immutability and the transfer of digital assets.
A database for the planet - Scot Chain Edinburgh - Nov 11, 2016BigchainDB
Bruce Pon, CEO of BigchainDB talks about a database for the planet and mass adoption. But to reach everyone, it will need scale and the possibility for interoperability with legacy systems.
Blockchain: The New Technology of TrustMarco Segato
An introductory presentation of the technology that is said to change the world, the result of practical research and participation in the Permanent Observatory of the Polytechnic University of Milan.
Bitcoin and blockchain are not the same things, although they are related in that blockchain technology was first described and implemented in Bitcoin. Learn More about Blockchain:
Shared on 5th Dec at SGInnovate with Swirlds Mance Harmon, Jordan Fried and Edgar Seah.
Hashgraph consensus, demo apps in Swirlds Java SDK, babble (unofficial golang implementation of Hashgraph) and their implications for distributed ledger technology.
Michal Mucha: Build and Deploy an End-to-end Streaming NLP Insight System | P...PyData
At this workshop, you will build your own messaging insights system - data ingestion from a live data source (Reddit), queueing, deploying a machine learning model, and serving messages with insights to your mobile phone!
Unit testing data with marbles - Jane Stewart Adams, Leif WalshPyData
In the same way that we need to make assertions about how code functions, we need to make assertions about data, and unit testing is a promising framework. In this talk, we'll explore what is unique about unit testing data, and see how Two Sigma's open source library Marbles addresses these unique challenges in several real-world scenarios.
The TileDB Array Data Storage Manager - Stavros Papadopoulos, Jake BolewskiPyData
TileDB is an open-source storage manager for multi-dimensional sparse and dense array data. It has a novel architecture that addresses some of the pain points in storing array data on “big-data” and “cloud” storage architectures. This talk will highlight TileDB’s design and its ability to integrate with analysis environments relevant to the PyData community such as Python, R, Julia, etc.
Using Embeddings to Understand the Variance and Evolution of Data Science... ...PyData
In this talk I will discuss exponential family embeddings, which are methods that extend the idea behind word embeddings to other data types. I will describe how we used dynamic embeddings to understand how data science skill-sets have transformed over the last 3 years using our large corpus of jobs. The key takeaway is that these models can enrich analysis of specialized datasets.
Deploying Data Science for Distribution of The New York Times - Anne BauerPyData
How many newspapers should be distributed to each store for sale every day? The data science group at The New York Times addresses this optimization problem using custom time series modeling and analytical solutions, while also incorporating qualitative business concerns. I'll describe our modeling and data engineering approaches, written in Python and hosted on Google Cloud Platform.
Graph Analytics - From the Whiteboard to Your Toolbox - Sam LermaPyData
However, the the graph theory jargon can make graph analytics seem more intimidating for self-study than is necessary. In this talk, the audience will be exposed to some of the basic concepts of graph theory (no prerequisite math knowledge needed!) and a few of the Python tools available for graph analysis.
Do Your Homework! Writing tests for Data Science and Stochastic Code - David ...PyData
To productionize data science work (and have it taken seriously by software engineers, CTOs, clients, or the open source community), you need to write tests! Except… how can you test code that performs nondeterministic tasks like natural language parsing and modeling? This talk presents an approach to testing probabilistic functions in code, illustrated with concrete examples written for Pytest.
RESTful Machine Learning with Flask and TensorFlow Serving - Carlo MazzaferroPyData
Those of us who use TensorFlow often focus on building the model that's most predictive, not the one that's most deployable. So how to put that hard work to work? In this talk, we'll walk through a strategy for taking your machine learning models from Jupyter Notebook into production and beyond.
Mining dockless bikeshare and dockless scootershare trip data - Stefanie Brod...PyData
In September 2017, dockless bikeshare joined the transportation options in the District of Columbia. In March 2018, scooter share followed. During the pilot of these technologies, Python has helped District Department of Transportation answer some critical questions. This talk will discuss how Python was used to answer research questions and how it supported the evaluation of this demonstration.
Avoiding Bad Database Surprises: Simulation and Scalability - Steven LottPyData
There are many stories of developers creating databases that don't operate at scale. The application is good, but the database won't work the realistic volumes of data. It's like a horror movie where they never looked behind the door, ran into the dark forest and night, and discovered the database was the monster killing their application. How can we leverage Python to avoid scaling problems?
Machine learning often requires us to think spatially and make choices about what it means for two instances to be close or far apart. So which is best - Euclidean? Manhattan? Cosine? It all depends! In this talk, we'll explore open source tools and visual diagnostic strategies for picking good distance metrics when doing machine learning on text.
End-to-End Machine learning pipelines for Python driven organizations - Nick ...PyData
The recent advances in machine learning and artificial intelligence are amazing! Yet, in order to have real value within a company, data scientists must be able to get their models off of their laptops and deployed within a company’s data pipelines and infrastructure. In this session, I'll demonstrate how one-off experiments can be transformed into scalable ML pipelines with minimal effort.
We will be using Beautiful Soup to Webscrape the IMDB website and create a function that will allow you to create a dictionary object on specific metadata of the IMDB profile for any IMDB ID you pass through as an argument.
1D Convolutional Neural Networks for Time Series Modeling - Nathan Janos, Jef...PyData
This talk describes an experimental approach to time series modeling using 1D convolution filter layers in a neural network architecture. This approach was developed at System1 for forecasting marketplace value of online advertising categories.
Extending Pandas with Custom Types - Will AydPyData
Pandas v.0.23 brought to life a new extension interface through which you can extend NumPy's type system. This talk will explain what that means in more detail and provide practical examples of how the new interface can be leveraged to drastically improve your reporting.
Machine learning models are increasingly used to make decisions that affect people’s lives. With this power comes a responsibility to ensure that model predictions are fair. In this talk I’ll introduce several common model fairness metrics, discuss their tradeoffs, and finally demonstrate their use with a case study analyzing anonymized data from one of Civis Analytics’s client engagements.
What's the Science in Data Science? - Skipper SeaboldPyData
The gold standard for validating any scientific assumption is to run an experiment. Data science isn’t any different. Unfortunately, it’s not always possible to design the perfect experiment. In this talk, we’ll take a realistic look at measurement using tools from the social sciences to conduct quasi-experiments with observational data.
Applying Statistical Modeling and Machine Learning to Perform Time-Series For...PyData
Forecasting time-series data has applications in many fields, including finance, health, etc. There are potential pitfalls when applying classic statistical and machine learning methods to time-series problems. This talk will give folks the basic toolbox to analyze time-series data and perform forecasting using statistical and machine learning models, as well as interpret and convey the outputs.
Solving very simple substitution ciphers algorithmically - Stephen Enright-WardPyData
A historical text may now be unreadable, because its language is unknown, or its script forgotten (or both), or because it was deliberately enciphered. Deciphering needs two steps: Identify the language, then map the unknown script to a familiar one. I’ll present an algorithm to solve a cartoon version of this problem, where the language is known, and the cipher is alphabet rearrangement.
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...PyData
Artificial intelligence is emerging as a new paradigm in materials science. This talk describes how physical intuition and (insightful) machine learning can solve the complicated task of structure recognition in materials at the nanoscale.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
9. “Big data” Distributed DBs
http://1.bp.blogspot.com/-ZFtW7MFMqZQ/TrG5ujuDGdI/AAAAAAAAAWw/heceeMD50x4/s1600/scale.png
Planetary scale:
Netflix uses 37% of
Internet bandwidth
Writes / s vs. # nodes
10. To be Distributed,
Big Data DBs Must Solve Consensus
Byzantine Consensus
(1982)
Paxos (1990/1998)
https://medium.com/the-bigchaindb-blog/the-writings-of-leslie-lamport-abridged-a67df77f464#.1lr34qt6s
http://the-paper-trail.org/blog/consensus-protocols-paxos/
11. Two ways to scale up
Big data-fy the blockchain
• Builds on man-decades of work
• Significant scalability hurdles?
<or>
Blockchain-ify big data
• Builds on man-centuries (millennia?) of work
• Scalability challenges already resolved
• How to blockchain-ify? …
12. “Blockchain-ify”
Decentralization: no single entity owns or controls
Immutability: tamper-resistant
Assets: Can issue & transfer assets
Blockchain (noun): hashed-together chain of blocks (1991!)
Blockchain (noun): storage that is decentralized + immutable + assets
Blockchain (adj): decentralized + immutable + assets
14. How to Blockchain-ify Big Data
Retain Big Data DB’s Performance
• Let the Paxos derivative solve order.
Get out of its way!
• It naturally builds a log of all txs
Add in blockchain characteristics
• Decentralization: federation voting
on txs. Group into blocks for speed.
• Immutability: hash on prev. blocks
• Assets: Digital signatures etc.
15. System Arch
BigchainDB Federation
RethinkDB Cluster
Alice
Bob
★ RethinkDB
handles intra-cluster
communication
★ BigchainDB Nodes
accept new transactions
via an API
★ BigchainDB Nodes
bundle transactions in
blocks and validate them
16. Two Tables
Transaction set S (“backlog”) Block chain C
txs when a
signing node
creates a new
block
txs when a
block has
invalid
transactions
tx G
tx A
tx L
tx H
tx E
tx C
tx D
S1
S2
S3
S C
null tx
tx G
B1
B2
tx L
tx A
tx H
B2
tx E
(genesis
block)
24. Users: ascribe.io, 5000 artists, 25
marketplaces & non-profits
Value Props: secure provenance
in $64B art industry, IP mgmt.
Verticals: Art Supply Chain,
Intellectual Property
