A SYSTEM AND METHOD FOR IMPLEMENTING DATA CONSISTENCY IN CLOUD-NATIVE DATABASES

Abstract

The invention relates to a system and method for implementing data consistency in cloud-native databases. Data is a highly sensitive resource for all the organizations. Maintaining the data consistency and security is the organization's is the primary requirement. It is also essential to lower the risk of data loss. The present system comprises BadgerDB to provide fully serializable transactions and read-intensive workloads, RAFT to offer fault tolerance and uniformity, and Jump Consistent Hash to ensure that key values are distributed equally across storage buckets. Further, Multi-Group RAFT provides more flexibility and scalability. High performance in data transactions without failures, enabled by these technologies.

Specification

Description:Field of the Invention
The present invention relates to the technical field of data management in distributed cloud-native databases, more particular to a system and method for implementing data consistency in cloud-native databases using a combination of BadgerDB, RAFT consensus protocol, Jump Consistent Hashing, and Multi-Group RAFT.
Background of the Invention
During large amount of data transactions on the server, server get failed down and data transaction process stops for sometimes. Thus, the organization suffers when server get down. All the banking transactions get on hold.
Abdelhafiz et al. (2020), The spread of databases via sharding, with the goal of increasing throughput and decreasing reaction time. The author discusses issues including monolithic architecture and unique requirements that arise with distributed databases. The advantages of Oracle sharding, which automates all shard life cycle tasks including deployment, schema development, and data routing, are highlighted in the paper's conclusion.
Wang, Jianrong, et al. (2019), Wang presents NRSS, a sharding strategy intended to address performance problems in blockchain systems caused by variations in nodes. In order to balance the percentage of honest and dishonest nodes in each committee, NRSS assesses node behavior and assigns a score based on prior performance. As a result, blockchain security and transaction throughput are improved. Evaluations conducted through experiments show how well NRSS works to increase transaction throughput and security.
Zheng, Peilin, et al. (2022), Zheng presents Aeolus, a cutting-edge method for improving permissioned blockchain systems' performance. Aeolus enables distributed and parallel transaction processing by extending a single blockchain peer into a cluster and leveraging distributed state update sharding. Aeolus beats current platforms, reaching over 100,000 TPS across 32 shards, according to a comparative investigation.
None of the prior art indicated above either alone or in combination with one another disclose what the present invention has disclosed.
To solve the above-mentioned problem, the present invention system and method used a combination of a few technologies, i.e. BadgerDB, RAFT and Consensus. Implementing Badger, which can be replicated across multiple instances to form a cluster, provides a consistent embedded key-value database solution in Go, addressing several critical issues. The below are the advantages of using the proposed invention:
• Through the Embedded DB in go, with clustering options, the system can perform any kind of transaction even with heavy load of data in milliseconds.
• No error will be there during the transaction and the system is completely reliable.
• Data consistency will be retained, and it strengthened the data transaction process.
• This designed system is scalable for various sizes of organizations; it will prevent data loss during server failure through the Raft and consensus algorithm.
Drawings
Figure 1 illustrates the working methodology of present invention.
Detailed Description of the Invention
The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.
In any embodiment described herein, the open-ended terms "comprising," "comprises," and the like (which are synonymous with "including," "having" and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like. As used herein, the singular forms "a", "an", and "the" designate both the singular and the plural, unless expressly stated to designate the singular only.
The invention proposes an improved method for implementing data consistency in cloud-native databases by integrating BadgerDB, RAFT consensus, Jump Consistent Hashing, and Multi-Group RAFT. This combination offers a robust solution for managing distributed data with enhanced fault tolerance, uniformity, scalability, and high performance.
• The BadgerDB is implemented to provide fully serializable transactions and read-intensive workloads.
• RAFT to offer fault tolerance and uniformity.
• Jump Consistent Hash to ensure that key values are distributed equally across storage buckets.
• Multi-Group RAFT provides more flexibility and scalability.
The method of the present invention comprises of three states: leader, candidate and follower. , and further includes the following steps:
• Any request made to a follower node is routed to the leader node, with the leader being the only node that communicates directly with the client;
• Each node maintains and propagates a term number during inter-node communication, and an election is conducted to select a new leader at the beginning of each term;
• A candidate solicits votes from follower nodes in order to obtain a majority vote, and if the majority is obtained, the candidate becomes the leader for the remainder of the current term;
• A command requested by the client is executed by the leader, with an index used to locate the entry point in the leader's log and a term number used to determine when the command was entered;
• If a majority is not obtained, the method restarts from the beginning.
This innovation is completely reliable, and it makes the performance of the data transaction fast.
Storing and retrieving data process done in milliseconds without any server failure. The author stored 1000 entries and retrieved same in one go.
If the load will be increased on server, then proposed system will be capable to handle that load without any failure with fast performance also.
The advantage of the invention is listed below:
• An implementation that makes use of BadgerDB, the RAFT algorithm, and consensus to improve the data transaction process. Its primary function is to control log replication consistency.
• This invention offers a way to stop data loss in cluster networks by using the RAFT algorithm with BadgerDB.
• Most applications and enterprises can be satisfied with consensus-based replication's performance.

, Claims:1. A system for implementing data consistency in cloud-native databases, comprises of:
• The BadgerDB is implemented to provide fully serializable transactions and read-intensive workloads.
• RAFT to offer fault tolerance and uniformity.
• Jump Consistent Hash to ensure that key values are distributed equally across storage buckets.
• Multi-Group RAFT provides more flexibility and scalability.
2. The system for implementing data consistency in cloud-native databases as claimed in the claim 1, wherein method comprises of three states: leader, candidate and follower, and further includes the following steps:
• Any request made to a follower node is routed to the leader node, with the leader being the only node that communicates directly with the client;
• Each node maintains and propagates a term number during inter-node communication, and an election is conducted to select a new leader at the beginning of each term;
• A candidate solicits votes from follower nodes in order to obtain a majority vote, and if the majority is obtained, the candidate becomes the leader for the remainder of the current term;
• A command requested by the client is executed by the leader, with an index used to locate the entry point in the leader's log and a term number used to determine when the command was entered;
• If a majority is not obtained, the method restarts from the beginning.
3. The system for implementing data consistency in cloud-native databases as claimed in the claim 1, wherein
• System is completely reliable, and it makes the performance of the data transaction fast.
• Storing and retrieving data process done in milliseconds without any server failure. The author stored 1000 entries and retrieved same in one go.
• If the load will be increased on server, then proposed system will be capable to handle that load without any failure with fast performance also.

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