We have come a long way since the times of a single database model to a cloud-based centralized database. This change has enhanced the user experience and drastically reduced the chances of failure (such as loss of data). Today, we are seeing another paradigm shift to a decentralized database model.
Let’s explore the challenges faced in the centralized database model, that can be resolved with a decentralized model along with some project examples.
Moment of truth:
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540 million Facebook user records stood exposed on the Amazon cloud server in 2019
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7.5 million Adobe Creative Cloud account information stood exposed on October 26, 2019
These statistics reflect the ways in which the centralized cloud database security setups can be flawed. Not a majority, but there are few soft spots that even giants like Facebook and Adobe are not able to plug. These shortcomings are acting as a catalyst. Effectively, decentralized cloud-based models, will hence change the way the enterprises and users store, exchange, and monetize data.
Building decentralized databases
Experts have been praising blockchains for being secure, immutable, and transparent databases. However, the fact is that blockchain can only hold very small amounts of data and they are very hard to query. In simple words, using blockchain as a database is neither efficient nor easy.
However, blockchain finds its use as a layer to build a highly efficient decentralized database solution. That is what projects like Sia, CyberVein, Streamr, Datum, and Omnilytics are trying to build. This article talks about these projects and their design principles. It also sheds light on how they are different from each other.
1. Sia – A distributed storage platform
Powered by blockchain Sia is a decentralized cloud storage platform. It operates on a peer to peer basis. With Sia, the storage seekers do not need to rely on any centralized cloud database. As a matter of fact, Sia connects the storage seekers (renters) with providers (hosts) in a decentralized P2P platform. Such a set up ensures higher data security as well.
If you have some underutilized storage (say some hard disks), you can become a host on the Sia platform. For this you can get incentivized for contributing your storage to the platform. When a renter (example an enterprise) uploads a file on Sia and the algorithm segments the file encrypts the segments. Using smart contracts, Sia ships these segments to different hosts.
In this manner, the Sia platform achieves the decentralization of storage. It uses Twofish algorithmic encryption for the security of these file segments. With such kind of set-up, there is no single point of failure and no centralized storage of data.
Pros
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The file segments are spread out across multiple storage devices. Thus even if a hacker takes control of a particular storage device, he will lay his hands only a part of the file which will be of no use to him.
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Sia team claims that content delivery is faster than centralized cloud databases. This is because the database is geographically spread out.
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A Sia user pays only $2 for 1 TB/ per month storage.
Cons
Sia is only a storage platform, the data exchange and monetization is not possible with it.
2. Streamr – Decentralized infrastructure for real-time data exchange
Streamr is creating a platform for the real-time data generated across the globe to be owned and traded by the data producers. It aims to build a decentralized P2P network for real-time data.
Along with the P2P platform, it brings users a marketplace to trade data and Data Unions for aggregated data trading.
At the core of Streamr are Broker nodes that contribute bandwidth and storage of the network. Using P2P set-up and incentivization, Streamr ensures a decentralized exchange of data.
It uses Ethereum blockchain for value settlement, permission control, reputation metric, and identity management. All the while the real-time data stays safe in the scalable Streamr Network (Broker Nodes).
Pros
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It comes with a Marketplace which is a web application. Using it the publishers and consumers can trade real-time data streams.
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Data Unions support crowd selling. It aggregates data from different publishers. Valuable insights are generated from this data and are sold to the consumers.
Cons
Streamr started as a centralized data exchange platform. It will incrementally move to decentralization in four different stages. According to the roadmap, the first decentralization will happen in 2020.
CyberVein – A data storage, exchange, and monetization platform
CyberVein has created a decentralized database ecosystem. It utilizes blockchain, DAG, and AI to store, trade, connect, and transform data. It is the PISR Consortium database that renders decentralization to the platform for data management. This also ensures the reliability of data resources using virtual machine operations.
By combining DAG and blockchain, CyberVein overcomes the certain shortcoming of blockchain technology. To state a few, longer transaction times and limited transaction speeds. While DAG acts as a back-up storage layer, it ensures there is no need for miners and no block confirmations are required. Effectively, the fees associated with data management and transfers are very low. However, this does not make CyberVein compromise its transaction speed. It must be noted that DAG is optional for businesses to use. But as each DAG node operates parallel to each other, it makes the network highly scalable.
No product of CyberVein touches the data. In fact, the data remains on the local databases where it is stored as 1s, 0s, or sharded files. By utilizing the unique Proof of Consensus mechanism, it ensures minimal energy expenditure to reach a consensus. Moreover, it incentivizes the storage contributors.
CyberVein enables data monetization with its Federated learning modules. This is an application layer that trains the datasets locally on a real-time basis. Thus opens up real-word data monetization opportunities for data suppliers.
Pros
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Using different modules, CyberVein proves to be an efficient data management tool also.
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As it stores the states of data, any non-permissioned change in data can be easily identified and controlled.
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As DAG stores the states of the decentralized database, it makes data recovery easy at any given point in time.
CyberVein offers a perfect platform to make the best use of aggregated data. Moreover, it does not compromise on security and privacy. According to the team, the final product is completely ready for mainnet launch.
Cons
The lack of adoption for federated learning-based data exchange is a challenge/con.
Datum – A Decentralized Storage Network
Datum is also a decentralized storage network. It uses Data Access Token (DAT) Smart contract to facilitate secure data trading. The terms are set out by the data owners using smart contracts.
The Datum platform users can store their data on the network for a small DAT token. After submitting the data and establishing terms of usage, the data is anonymized. This data is then sent to the network for storage. The storage node miners of the Datum network are responsible for saving and transmitting the encrypted data. In case a buyer wants to acquire the data, the smart contracts initiate the off-chain key exchange.
Datum has been working hard to revamp the scalability and speed of data transfer. But not at the cost of compromising the decentralization of the network. Last year it launched Datum Drive which is accessible just like a Google Drive. For storage of a file, Datum Drive breaks files into small chunks. For each chunk, a hash is calculated which is then arranged in a Merkle tree model.
Pros
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Datum supports data saving, sharing, storing and accessing using DAT tokens
Cons
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As each hash is committed to the blockchain, this creates a scalability challenge. Currently, Datum blockchain support only 15 TPS. This is quite less to serve users at the enterprise level.
Omnilytics – Intelligent data aggregator using blockchain
The Omnilytics is a distributed data network that processes global aggregated datasets. It uses blockchain, artificial intelligence, and big data analytics to serve various industries. Using AI, it makes the most of its big data pool, and the insights are used for efficient marketing, auditing, and trend forecasting.
Omnilytics has architected a distributed data network using blockchain technology. The blockchain facilitates the use of smart contracts, distributed data fingerprinting, and data exchange on Omnilytics. The usage of blockchain ensures the data provided to the community is verified. On top of it, the data exchange is always transparent.
The Omnilytics platform uses five different types of nodes throughout its architecture:
Data-Shaper Nodes:
These retail nodes shape the data into a structured format using AI techniques.
Data-Shaper Supernodes:
These data scientists or corporations normalize large data sets using existing AI models.
Data-Acquisition Nodes:
Ensures only high-quality data acquisition. The data consumption is tracked on the blockchain.
Data-Acquisition Supernodes:
These are big corporations that help acquire only credible data and track the consumption of data using blockchain.
Data -Validation Nodes:
These are retail nodes that create data fingerprints and validate the data’s checksum. This cryptographic hash is stored on the decentralized database and ensures data immutability.
The users for the data on Omnilytics get in touch with the Platform Coordinator to process the requests he has made to the Data Acquisition nodes. The Data Validation Nodes then validate the acquired data. This data is then normalized by the Data Sharper Nodes. In the end, the data is sent to the end-user for which he pays OMN tokens.
Pros
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Data partners can track the performance of their data. Using this methodology, the pricing remains competitive
Cons
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It is a platform with a great vision but we do not see much development happening
Final Takeaway
The shift from centralized database models to decentralized database models will give birth to a plethora of new opportunities. The need of the hour is a platform that enables storage, exchange as well as monetization of the accumulated data. From this perspective, CyberVein is an enterprise-ready solution and leads ahead of Sia, Streamr, Omnilytics, and Datum.
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