BigchainDB vs Cassandra

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

BigchainDB

Stacks27

Followers71

Votes0

GitHub Stars4.0K

Forks769

BigchainDB vs Cassandra: What are the differences?

Introduction

In this article, we will discuss the key differences between BigchainDB and Cassandra. Both BigchainDB and Cassandra are databases that serve different purposes and have distinct features. Below are the key differences between the two:

Data Model: BigchainDB uses a blockchain-based data model, while Cassandra uses a distributed data model. BigchainDB provides immutability, transparency, and decentralization through blockchain technology, making it ideal for scenarios where there is a need for tamper-proof records and distributed control. On the other hand, Cassandra is designed for high availability and scalability, making it suitable for applications that require handling large amounts of data with low latency.
Consensus Algorithm: BigchainDB uses a consensus algorithm called "Proof of Authority" (PoA), where a select group of nodes are designated as validators to achieve consensus on transactions. Cassandra, on the other hand, uses a distributed consensus algorithm called "Hinted Handoff" to ensure data consistency and availability across multiple nodes. The difference in consensus algorithms affects the performance, scalability, and trust model of the two databases.
Scalability: BigchainDB and Cassandra differ in their scalability approaches. BigchainDB achieves scalability by sharding the data across multiple nodes, allowing for linear scalability as the network grows. Cassandra, on the other hand, achieves scalability by using a peer-to-peer architecture where data is partitioned and replicated across multiple nodes based on a consistent hashing algorithm. This distributed architecture allows Cassandra to handle large amounts of data and provide high availability.
Query Language: BigchainDB uses a custom query language called "Bigchain Query Language" (BQL) to interact with the database. BQL provides a way to query and filter data using a JSON-based syntax. Cassandra, on the other hand, uses Cassandra Query Language (CQL), which is similar to SQL but optimized for distributed environments. The difference in query languages may require developers to learn and adapt to the specific syntax and features of each database.
Data Consistency: BigchainDB guarantees data consistency through the use of blockchain technology, where transactions are sequentially ordered and verified by a consensus algorithm. This ensures that all nodes in the network have a consistent view of the data. Cassandra, on the other hand, provides tunable consistency, allowing developers to configure the level of consistency they need for their applications. This flexibility comes at the cost of potential data conflicts in certain scenarios.
Use Cases: BigchainDB is well-suited for use cases that require data immutability, transparency, and decentralized control, such as supply chain management, digital identity, and intellectual property rights management. Cassandra, on the other hand, is ideal for use cases that require high availability, scalability, and low-latency data access, such as time series data, real-time analytics, and content management systems.

In summary, BigchainDB and Cassandra differ in their data models, consensus algorithms, scalability approaches, query languages, data consistency mechanisms, and use cases. While BigchainDB leverages blockchain technology for immutability and decentralization, Cassandra focuses on high availability and scalability in a distributed environment.

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Advice on Cassandra, BigchainDB

Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

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Detailed Comparison

Cassandra	BigchainDB
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.	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.
-	Decentralization; Immutability; Native Support of Multiassets; Byzantine Fault Tolerant (BFT); Low Latency; Traditional Stack
Statistics
GitHub Stars 9.5K	GitHub Stars 4.0K
GitHub Forks 3.8K	GitHub Forks 769
Stacks 3.6K	Stacks 27
Followers 3.5K	Followers 71
Votes 507	Votes 0
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Size 1 Updates	No community feedback yet
Integrations
No integrations available	Golang Python C++ Blockchain Wagyu

What are some alternatives to Cassandra, BigchainDB?

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

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

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.

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

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 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

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.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

BigchainDB vs Cassandra: What are the differences?

Introduction

Data Model: BigchainDB uses a blockchain-based data model, while Cassandra uses a distributed data model. BigchainDB provides immutability, transparency, and decentralization through blockchain technology, making it ideal for scenarios where there is a need for tamper-proof records and distributed control. On the other hand, Cassandra is designed for high availability and scalability, making it suitable for applications that require handling large amounts of data with low latency.
Consensus Algorithm: BigchainDB uses a consensus algorithm called "Proof of Authority" (PoA), where a select group of nodes are designated as validators to achieve consensus on transactions. Cassandra, on the other hand, uses a distributed consensus algorithm called "Hinted Handoff" to ensure data consistency and availability across multiple nodes. The difference in consensus algorithms affects the performance, scalability, and trust model of the two databases.
Scalability: BigchainDB and Cassandra differ in their scalability approaches. BigchainDB achieves scalability by sharding the data across multiple nodes, allowing for linear scalability as the network grows. Cassandra, on the other hand, achieves scalability by using a peer-to-peer architecture where data is partitioned and replicated across multiple nodes based on a consistent hashing algorithm. This distributed architecture allows Cassandra to handle large amounts of data and provide high availability.
Query Language: BigchainDB uses a custom query language called "Bigchain Query Language" (BQL) to interact with the database. BQL provides a way to query and filter data using a JSON-based syntax. Cassandra, on the other hand, uses Cassandra Query Language (CQL), which is similar to SQL but optimized for distributed environments. The difference in query languages may require developers to learn and adapt to the specific syntax and features of each database.
Data Consistency: BigchainDB guarantees data consistency through the use of blockchain technology, where transactions are sequentially ordered and verified by a consensus algorithm. This ensures that all nodes in the network have a consistent view of the data. Cassandra, on the other hand, provides tunable consistency, allowing developers to configure the level of consistency they need for their applications. This flexibility comes at the cost of potential data conflicts in certain scenarios.
Use Cases: BigchainDB is well-suited for use cases that require data immutability, transparency, and decentralized control, such as supply chain management, digital identity, and intellectual property rights management. Cassandra, on the other hand, is ideal for use cases that require high availability, scalability, and low-latency data access, such as time series data, real-time analytics, and content management systems.

BigchainDB vs Cassandra

Overview

BigchainDB vs Cassandra: What are the differences?