Cassandra vs Snowflake

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

Snowflake

Stacks1.2K

Followers1.2K

Votes27

Cassandra vs Snowflake: What are the differences?

Introduction

Cassandra and Snowflake are both popular databases used for storing and processing data, but they have some key differences in their architecture and use cases.

Data Model: Cassandra is a NoSQL database that uses a columnar data model, allowing for flexible schema and efficient write operations. On the other hand, Snowflake is a relational database that follows the traditional relational model with tables, rows, and columns.
Scalability: Cassandra is designed for high scalability and distributed architecture, making it suitable for handling large amounts of data and high write and read loads. Snowflake, on the other hand, provides elasticity by automatically scaling up or down compute resources as needed, which is more suitable for ad-hoc querying and analytics workloads.
Data Processing: Cassandra is optimized for fast write operations and can handle real-time data ingestion and high-speed data writes. It is well-suited for use cases requiring low-latency data updates. Snowflake, on the other hand, excels in complex analytics and reporting scenarios, providing advanced SQL querying capabilities and support for joining and aggregating large datasets.
Data Consistency: Cassandra offers tunable consistency, allowing users to choose between eventual consistency or strong consistency levels based on their requirements. Snowflake provides strong consistency guarantees, ensuring that all queries see the most recent data.
Query Language: Cassandra uses CQL (Cassandra Query Language), which is a SQL-like language. It also provides a limited set of predefined functions and does not support complex joins or transactions. Snowflake uses standard SQL for querying data and supports advanced SQL features like window functions, subqueries, and complex joins.
Data Storage: Cassandra stores data in a distributed fashion across multiple nodes, ensuring high availability and fault tolerance. It uses a peer-to-peer gossip protocol for communication between nodes. Snowflake, on the other hand, uses a shared virtual warehouse architecture and separates storage from compute, allowing for independent scaling of storage and compute resources.

In Summary, Cassandra is a scalable NoSQL database optimized for fast writes and low-latency data updates, while Snowflake is a relational database designed for complex analytics and reporting workloads with automatic scaling capabilities.

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Advice on Cassandra, Snowflake

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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Comments

Detailed Comparison

Cassandra	Snowflake
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.	Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
Statistics
GitHub Stars 9.5K	GitHub Stars -
GitHub Forks 3.8K	GitHub Forks -
Stacks 3.6K	Stacks 1.2K
Followers 3.5K	Followers 1.2K
Votes 507	Votes 27
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 7 Public and Private Data Sharing 4 User Friendly 4 Good Performance 4 Multicloud 3 Great Documentation
Integrations
No integrations available	Python Apache Spark Node.js Looker Periscope Mode

What are some alternatives to Cassandra, Snowflake?

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

Cassandra vs Snowflake: What are the differences?

Introduction

Cassandra and Snowflake are both popular databases used for storing and processing data, but they have some key differences in their architecture and use cases.

Data Model: Cassandra is a NoSQL database that uses a columnar data model, allowing for flexible schema and efficient write operations. On the other hand, Snowflake is a relational database that follows the traditional relational model with tables, rows, and columns.
Scalability: Cassandra is designed for high scalability and distributed architecture, making it suitable for handling large amounts of data and high write and read loads. Snowflake, on the other hand, provides elasticity by automatically scaling up or down compute resources as needed, which is more suitable for ad-hoc querying and analytics workloads.
Data Processing: Cassandra is optimized for fast write operations and can handle real-time data ingestion and high-speed data writes. It is well-suited for use cases requiring low-latency data updates. Snowflake, on the other hand, excels in complex analytics and reporting scenarios, providing advanced SQL querying capabilities and support for joining and aggregating large datasets.
Data Consistency: Cassandra offers tunable consistency, allowing users to choose between eventual consistency or strong consistency levels based on their requirements. Snowflake provides strong consistency guarantees, ensuring that all queries see the most recent data.
Query Language: Cassandra uses CQL (Cassandra Query Language), which is a SQL-like language. It also provides a limited set of predefined functions and does not support complex joins or transactions. Snowflake uses standard SQL for querying data and supports advanced SQL features like window functions, subqueries, and complex joins.
Data Storage: Cassandra stores data in a distributed fashion across multiple nodes, ensuring high availability and fault tolerance. It uses a peer-to-peer gossip protocol for communication between nodes. Snowflake, on the other hand, uses a shared virtual warehouse architecture and separates storage from compute, allowing for independent scaling of storage and compute resources.

Cassandra vs Snowflake

Overview