StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Cassandra vs VoltDB

Cassandra vs VoltDB

OverviewDecisionsComparisonAlternatives

Overview

Cassandra
Cassandra
Stacks3.6K
Followers3.5K
Votes507
GitHub Stars9.5K
Forks3.8K
VoltDB
VoltDB
Stacks18
Followers72
Votes18

Cassandra vs VoltDB: What are the differences?

# Introduction
In this comparison, we will highlight the key differences between Cassandra and VoltDB, two popular databases in the industry.

1. **Data Model**: Cassandra is a wide-column store NoSQL database that uses a decentralized architecture, perfect for handling massive amounts of data across multiple nodes. On the other hand, VoltDB is an in-memory operational database that stores data in memory for faster processing, making it ideal for real-time applications where low-latency is crucial.
2. **Consistency**: Cassandra offers eventual consistency, meaning that updates to the database may take some time to propagate across all nodes, leading to potential data divergence temporarily. In contrast, VoltDB provides strong consistency, ensuring that all nodes have the same data at any given moment, making it more reliable for critical operations that require data accuracy.
3. **Scalability**: Cassandra provides linear scalability by adding more nodes to the cluster, allowing it to handle growing workloads effortlessly. VoltDB, on the other hand, scales vertically by adding more resources to the server, making it easier to manage for smaller deployments with lower hardware requirements.
4. **Use Case**: Cassandra is well-suited for applications requiring high availability, fault tolerance, and scalability, such as social media platforms and IoT devices. VoltDB, with its emphasis on real-time processing, is best suited for applications that demand ultra-low latency, such as financial trading platforms and telecommunications systems.
5. **Architecture**: Cassandra follows a masterless architecture where all nodes are equal, allowing for high availability and fault tolerance. In contrast, VoltDB utilizes a shared-nothing architecture where each node operates independently, minimizing inter-node communication overhead and ensuring rapid processing speed.
6. **Consolidation**: While Cassandra is designed for horizontal scaling across multiple nodes to handle vast amounts of data, VoltDB focuses on consolidating data processing in-memory on a single server, making it more suitable for real-time analytics and transactional workloads that require lightning-fast response times. 

# Summary
In summary, Cassandra and VoltDB differ in their data models, consistency levels, scalability options, use cases, architectures, and approaches to data processing, making them suitable for distinct types of applications depending on specific requirements.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Cassandra, VoltDB

Vinay
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.

174k views174k
Comments

Detailed Comparison

Cassandra
Cassandra
VoltDB
VoltDB

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.

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

-
In-Memory Performance with On-Disk Durability;Transparent Scalability with Data Consistency;NewSQL – All the benefits of SQL with Unlimited Scalability;JSON Support for Agile Development;ACID Compliant Transactions;Export Data to OLAP Stores and Data Warehouses
Statistics
GitHub Stars
9.5K
GitHub Stars
-
GitHub Forks
3.8K
GitHub Forks
-
Stacks
3.6K
Stacks
18
Followers
3.5K
Followers
72
Votes
507
Votes
18
Pros & Cons
Pros
  • 119
    Distributed
  • 98
    High performance
  • 81
    High availability
  • 74
    Easy scalability
  • 53
    Replication
Cons
  • 3
    Reliability of replication
  • 1
    Updates
  • 1
    Size
Pros
  • 5
    SQL + Java
  • 4
    In-memory database
  • 4
    A brainchild of Michael Stonebraker
  • 3
    Very Fast
  • 2
    NewSQL

What are some alternatives to Cassandra, VoltDB?

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.

Redis

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase