Cassandra vs Google Cloud Spanner

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

Google Cloud Spanner

Stacks57

Followers117

Votes3

GitHub Stars2.0K

Forks1.1K

Cassandra vs Google Cloud Spanner: What are the differences?

Introduction: Cassandra and Google Cloud Spanner are both widely used and powerful distributed database systems. However, they differ in several key aspects. This article aims to highlight the key differences between Cassandra and Google Cloud Spanner.

Data Model: Cassandra is a NoSQL database that follows a columnar data model, while Google Cloud Spanner is a globally distributed relational database with support for strong consistency. This means Cassandra is schema-less and allows flexible data modeling, while Spanner enforces a relational model with schemas and relationships between tables.
Scalability: Cassandra is designed for massive scalability and can easily handle a large amount of data and high traffic workloads. It can distribute data across multiple nodes in a cluster for improved performance and fault tolerance. On the other hand, while Spanner is also designed for scalability, it provides automatic scaling within predefined limits and offers global consistency, which comes with additional coordination overhead.
Consistency Model: Cassandra follows a tunable consistency model, which allows choosing the level of consistency between replicas based on performance and reliability requirements. It provides eventual consistency by default but can be configured for strong consistency if needed. In contrast, Spanner offers strong consistency globally, ensuring that all replicas see the same consistent data at all times.
Query Language: Cassandra uses Cassandra Query Language (CQL), which is similar to SQL but has some differences due to its NoSQL nature. It supports querying using CQL statements and has built-in support for secondary indexes. On the other hand, Spanner supports SQL-like queries with its own enhancements for distributed querying and scale. It provides transactional SQL semantics and supports powerful features like joins, indexing, and multi-version concurrency control.
Architecture: Cassandra follows a masterless distributed architecture, where all nodes in the cluster are equal peers. It uses a peer-to-peer gossip protocol for coordination and event dissemination. Spanner, on the other hand, has a distributed architecture with a single-node leader and multiple followers. It uses the Paxos algorithm for consensus and replication to ensure consistency and fault tolerance.
Pricing Model: Cassandra is an open-source project and can be used without any licensing fees. However, the cost of running and managing a Cassandra cluster can vary based on factors like infrastructure costs, maintenance efforts, and support requirements. Google Cloud Spanner, being a managed service, has a usage-based pricing model that considers factors like the number of nodes, storage, and data transfer. It provides automatic replication and maintenance, reducing the operational overhead for users.

In summary, Cassandra is a highly scalable, schema-less NoSQL database with tunable consistency and a flexible data model. Google Cloud Spanner is a globally distributed relational database with strong consistency, automatic scaling, and transactional SQL semantics. The choice between the two depends on the specific requirements of the application, such as data model flexibility, consistency needs, scalability, query language preference, and cost considerations.

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Advice on Cassandra, Google Cloud Spanner

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	Google Cloud Spanner
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 a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.
-	Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars 9.5K	GitHub Stars 2.0K
GitHub Forks 3.8K	GitHub Forks 1.1K
Stacks 3.6K	Stacks 57
Followers 3.5K	Followers 117
Votes 507	Votes 3
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	Pros 1 Scalable 1 Horizontal scaling 1 Strongly consistent
Integrations
No integrations available	MySQL PostgreSQL MongoDB SQLite

What are some alternatives to Cassandra, Google Cloud Spanner?

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 Google Cloud Spanner: What are the differences?

Data Model: Cassandra is a NoSQL database that follows a columnar data model, while Google Cloud Spanner is a globally distributed relational database with support for strong consistency. This means Cassandra is schema-less and allows flexible data modeling, while Spanner enforces a relational model with schemas and relationships between tables.
Scalability: Cassandra is designed for massive scalability and can easily handle a large amount of data and high traffic workloads. It can distribute data across multiple nodes in a cluster for improved performance and fault tolerance. On the other hand, while Spanner is also designed for scalability, it provides automatic scaling within predefined limits and offers global consistency, which comes with additional coordination overhead.
Consistency Model: Cassandra follows a tunable consistency model, which allows choosing the level of consistency between replicas based on performance and reliability requirements. It provides eventual consistency by default but can be configured for strong consistency if needed. In contrast, Spanner offers strong consistency globally, ensuring that all replicas see the same consistent data at all times.
Query Language: Cassandra uses Cassandra Query Language (CQL), which is similar to SQL but has some differences due to its NoSQL nature. It supports querying using CQL statements and has built-in support for secondary indexes. On the other hand, Spanner supports SQL-like queries with its own enhancements for distributed querying and scale. It provides transactional SQL semantics and supports powerful features like joins, indexing, and multi-version concurrency control.
Architecture: Cassandra follows a masterless distributed architecture, where all nodes in the cluster are equal peers. It uses a peer-to-peer gossip protocol for coordination and event dissemination. Spanner, on the other hand, has a distributed architecture with a single-node leader and multiple followers. It uses the Paxos algorithm for consensus and replication to ensure consistency and fault tolerance.
Pricing Model: Cassandra is an open-source project and can be used without any licensing fees. However, the cost of running and managing a Cassandra cluster can vary based on factors like infrastructure costs, maintenance efforts, and support requirements. Google Cloud Spanner, being a managed service, has a usage-based pricing model that considers factors like the number of nodes, storage, and data transfer. It provides automatic replication and maintenance, reducing the operational overhead for users.

Cassandra vs Google Cloud Spanner

Overview