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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Cassandra vs MonetDB

Cassandra vs MonetDB

OverviewDecisionsComparisonAlternatives

Overview

Cassandra
Cassandra
Stacks3.6K
Followers3.5K
Votes507
GitHub Stars9.5K
Forks3.8K
MonetDB
MonetDB
Stacks13
Followers35
Votes2

Cassandra vs MonetDB: What are the differences?

## Introduction:
When choosing a database management system, it's crucial to understand the key differences between options like Cassandra and MonetDB. Here are the main differentiators between the two.

1. **Data Model**: Cassandra is a NoSQL database that uses a column-family data model, allowing for flexible schemas and horizontal scalability. On the other hand, MonetDB is a relational database that utilizes a traditional table-based data model with predefined schemas.
 
2. **Query Language**: Cassandra uses Cassandra Query Language (CQL) which is similar to SQL but has its own syntax and limitations due to its distributed architecture. MonetDB, being a relational database, uses standard SQL for querying, making it easier for users familiar with SQL to work with the database.

3. **Storage Format**: In Cassandra, data is stored in a wide-column format, optimized for write-heavy workloads and horizontal scaling. MonetDB, on the other hand, stores data in columnar format, offering better performance for analytical queries and aggregation operations.

4. **Consistency Model**: Cassandra employs eventual consistency by default, meaning that updates may not be immediately reflected across all nodes in the cluster. MonetDB, being an ACID-compliant relational database, ensures strong consistency by default, making it suitable for use cases where data integrity is a priority.

5. **Performance**: Cassandra is designed for high availability and fault-tolerance, making it suitable for applications requiring constant uptime and high availability. MonetDB, being optimized for analytical workloads, offers superior performance for complex queries and data analysis tasks.

6. **Use Cases**: Cassandra is often used for real-time applications, IoT, and big data analytics due to its scalability and fault-tolerance. MonetDB, on the other hand, is well-suited for OLAP (Online Analytical Processing) applications, data warehousing, and business intelligence tasks where complex queries and data aggregation are common.

In Summary, understanding the key differences between Cassandra and MonetDB in terms of data model, query language, storage format, consistency model, performance, and use cases can help in making an informed decision based on specific requirements and use cases.

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Advice on Cassandra, MonetDB

Umair
Umair

Technical Architect at ERP Studio

Feb 12, 2021

Needs adviceonPostgreSQLPostgreSQLTimescaleDBTimescaleDBDruidDruid

Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

462k views462k
Comments
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
MonetDB
MonetDB

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.

MonetDB innovates at all layers of a DBMS, e.g. a storage model based on vertical fragmentation, a modern CPU-tuned query execution architecture, automatic and self-tuning indexes, run-time query optimization, and a modular software architecture.

Statistics
GitHub Stars
9.5K
GitHub Stars
-
GitHub Forks
3.8K
GitHub Forks
-
Stacks
3.6K
Stacks
13
Followers
3.5K
Followers
35
Votes
507
Votes
2
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
  • 2
    High Performance

What are some alternatives to Cassandra, MonetDB?

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.

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.

InfluxDB

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.

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