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  1. Stackups
  2. Application & Data
  3. Databases
  4. Blockchain
  5. Amazon QLDB vs BigchainDB

Amazon QLDB vs BigchainDB

OverviewComparisonAlternatives

Overview

BigchainDB
BigchainDB
Stacks27
Followers71
Votes0
GitHub Stars4.0K
Forks769
Amazon QLDB
Amazon QLDB
Stacks5
Followers17
Votes0

Amazon QLDB vs BigchainDB: What are the differences?

Introduction

Amazon QLDB and BigchainDB are both distributed ledger technologies that offer solutions for managing data in a decentralized and secure manner. However, there are key differences between the two.

1. Consensus Algorithm:

Amazon QLDB uses a centralized consensus algorithm called CDC (Controlled Diffusion Consensus) that allows for immediate finality of transactions. This means that once a transaction is committed, it is immediately considered as final and cannot be reversed.

On the other hand, BigchainDB uses a decentralized consensus algorithm that is based on a variant of the Proof of Stake (PoS) mechanism. This allows for a more distributed control over the network, but with a longer confirmation time for transactions.

2. Scalability:

Amazon QLDB provides a highly scalable solution for managing and querying large datasets. It uses an append-only data structure and an indexing mechanism that enables fast and efficient data retrieval. Additionally, QLDB offers a serverless architecture that allows for automatic scaling and does not require manual management of resources.

In contrast, BigchainDB uses a sharded architecture that allows for horizontal scaling across multiple nodes. It can handle a high volume of transactions and provides a scalable solution for managing and querying data.

3. Data Immutability:

Amazon QLDB ensures the immutability of data by using cryptographic hashes and chaining data blocks together. Once a block is committed to the ledger, it cannot be modified or deleted. This makes QLDB suitable for applications that require an immutable audit trail.

On the other hand, BigchainDB allows for data modification by providing a flexible data model. It allows for updates and changes to data records, making it more suitable for applications that require flexibility in managing data.

4. Transaction Throughput:

Amazon QLDB provides high transaction throughput and can handle thousands of transactions per second. This makes it suitable for applications that require real-time transaction processing.

BigchainDB, on the other hand, has a lower transaction throughput compared to QLDB. It can handle hundreds of transactions per second, which makes it suitable for applications that do not require real-time transaction processing.

5. Data Privacy:

Amazon QLDB provides data privacy by utilizing a centralized access control mechanism. Only authorized users have access to the data, and all actions on the ledger are tracked and audited.

BigchainDB, on the other hand, provides a more decentralized approach to data privacy. It allows for the creation of private and anonymous transactions, where the identities of the participants can be masked, providing a higher level of privacy.

6. Integration with Other Services:

Amazon QLDB is part of the larger suite of AWS services, which allows for seamless integration with other AWS services such as Amazon S3, Lambda, and CloudWatch. This enables developers to build end-to-end solutions without the need for complex integration work.

BigchainDB, on the other hand, can be integrated with various databases and blockchain frameworks, providing a more versatile solution for building applications.

In Summary, Amazon QLDB offers immediate finality of transactions with high scalability, data immutability, and data privacy. It provides seamless integration with other AWS services. On the other hand, BigchainDB offers a decentralized consensus algorithm, scalability through sharding, flexibility in managing data, and the ability to handle private and anonymous transactions.

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Detailed Comparison

BigchainDB
BigchainDB
Amazon QLDB
Amazon QLDB

It is designed to merge the best of two worlds: the “traditional” distributed database world and the “traditional” blockchain world. With high throughput, low latency, powerful query functionality, decentralized control, immutable data storage and built-in asset support.

It is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log ‎owned by a central trusted authority. It can be used to track each and every application data change and maintains a complete and verifiable history of changes over time.

Decentralization; Immutability; Native Support of Multiassets; Byzantine Fault Tolerant (BFT); Low Latency; Traditional Stack
Immutable and Transparent; Cryptographically Verifiable; Serverless; Easy to Use; Streaming Capability
Statistics
GitHub Stars
4.0K
GitHub Stars
-
GitHub Forks
769
GitHub Forks
-
Stacks
27
Stacks
5
Followers
71
Followers
17
Votes
0
Votes
0
Integrations
Golang
Golang
Python
Python
C++
C++
Blockchain
Blockchain
Wagyu
Wagyu
AWS Lambda
AWS Lambda
Amazon Redshift
Amazon Redshift
Amazon Kinesis
Amazon Kinesis
Amazon Elasticsearch Service
Amazon Elasticsearch Service

What are some alternatives to BigchainDB, Amazon QLDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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