Major Features of Bluzelle and Its Use case
Bluzelle takes blockchain principles and sharding & par22oning concepts to create an AirBnB like marketplace for data storage and management. This is a crypto-economic network of powerful producers and consumers.
Consumers
The consumer is the one who “consumes” the Bluzelle database services. Consumers are spending Bluzelle tokens so they can store and retrieve data. Addi_onally a user could get a credit of tokens if a producer failed to meet certain service levels.
Producer
The producer is the one who provides resources to the network in return for earning Bluzelle tokens (BLZ). Bluzelle producers will be required to put up a propor_onal stake of Bluzelle tokens, in order to provide a guarantee on the service levels Bluzelle will provide.
Bluzelle will encourage competition by producers to provide higher quality services, where those with higher service levels can charge more but also have to put up a higher stake. Every participating consumer and producer of Bluzelle are initially required to independently create their own Ethereum account and take responsibility for securing and protecting their private key. The private key is used to secure access to their ETH and Bluzelle tokens and encrypt their data before it gets sent out over the Bluzelle network.
DAPP USE CASES FOR BLUZELLE
Predictions Markets
Decentralized predictions markets on Ethereum require the management and storage of massive amounts of data to work.
These include:
(1) the questions being asked
(2) the different possible outcomes
(3) the predictions being made
(4) the sourced information for the actual events.
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A decentralized database can grow and scale as per the products needs. Having fast and reliable access to data is important for the success of the predic2ons market to garner new customers and participation.
Historical data stored on Bluzelle will add a new category of predictions that can reduce human speculation by using past events to make beter predictions.
Currency Exchange Protocols
A key part of a currency exchange protocol is the presence of relayers, who enable makers and takers to connect via off-chain order books. The underlying order-books must be fast, efficient, reliable, and easy to supply, by the relayers.
A pain point is relayers are responsible to store these order-books each in their own way. By using a decentralized database like Bluzelle, currency exchange protocols can provide relayers with a standard, consistent, ubiquitous, database that would be available with no effort. This reduction in friction maximizes the service level and quality as the network would now still be powered by relayers.
Data Streaming Networks
Data streaming networks match up consumers of data points with producers of data points. For example a car uses real-time traffic data from the data streaming network. The car collects real-time data while it moves. It is both paying for data it “buys” and “earning” from data it “sells” to the network. The data points need to be both readable and writable with high performance, availability, scalability, and reliability.
Bluzelle is ideal to provide the precise infrastructure needed so that a data streaming network can store its data to meet these requirements.
BLUZELLE FEATURES
Bluzelle is a decentralized database service for dApp developers. To ensure developers get the highest throughout in performance, reliability and scalability, Bluzelle implements swarming technologies. A swarm is a large group of nodes (computers) that work together to store and manage data. Nodes in these swarms can go down and new nodes can come up with minimal impact on the network. Overall Bluzelle is a meta-swarm comprised of multiple swarms.
Performance
Bluzelle’s unique and proprietary swarming techniques were designed for the highest performance. Bluzelle can reduce latency by retrieving data from the nearest nodes on the leaf swarm, and/or increase speed manyfold by retrieving data in parallel from the fastest nodes on the leaf swarm. This is like torrents and seeds. When data is requested, it is done in parallel where chunks (shards) are requested from all the different swarms that contain those shards, and these are all retrieved in parallel, resulting in desirable performance metrics.
Reliability
Using the concept of fog or swarm computing, Bluzelle follows a model where every unit of data is 100% replicated in a single leaf swarm amongst a swarm of swarms. So while the data is only in one swarm, that swarm’s nodes are aplenty and are geographically dispersed, immune to localized outages caused by either natural or human-related events.
Scalability
Scalability is possible both horizontally or ver_cally. Bluzelle manages the various strategies and considera_ons around the use case of having to increase scale. Horizontal scaling is a cornerstone of the Bluzelle architecture, where every swarm is another “unit” of horizontal scaling at the metaswarm level. Within every leaf swarm, every node acts as yet another agent of horizontal scaling, at the leaf swarm level.
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