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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Citus vs Google Cloud Spanner

Citus vs Google Cloud Spanner

OverviewComparisonAlternatives

Overview

Citus
Citus
Stacks60
Followers124
Votes11
GitHub Stars12.0K
Forks736
Google Cloud Spanner
Google Cloud Spanner
Stacks57
Followers117
Votes3
GitHub Stars2.0K
Forks1.1K

Citus vs Google Cloud Spanner: What are the differences?

Introduction

Citus and Google Cloud Spanner are both distributed database systems that provide scalability and high availability for applications. However, there are several key differences between Citus and Google Cloud Spanner that set them apart from each other.

  1. Data Model:

    • Citus is an extension to PostgreSQL, which means it inherits the same relational data model. It allows users to distribute tables across multiple nodes and use SQL for querying and modeling data.
    • Google Cloud Spanner, on the other hand, is a globally distributed relational database service. It provides a schema-based data model, but unlike Citus, it uses a semi-relational data model where data is structured as tables but also has hierarchical data types for structured data.
  2. Scalability:

    • Citus uses sharding to horizontally scale the database by distributing data across multiple nodes. It allows users to scale out their database by adding more nodes.
    • Google Cloud Spanner also supports horizontal scaling, but it uses a different approach called "TrueTime" that offers strong consistency across geographically distributed regions. It automatically splits and replicates data across multiple nodes to provide high scalability.
  3. Consistency Model:

    • Citus provides strong consistency within each shard, but it does not automatically provide strong consistency across all shards. Users can choose to enforce strong consistency at the application level if required.
    • Google Cloud Spanner guarantees external consistency, which means it provides strong consistency across all replicas and regions. It uses distributed transactions and a globally synchronized clock to ensure consistency.
  4. Query Language:

    • Citus extends PostgreSQL, so it supports the same SQL query language and allows users to leverage the rich ecosystem of PostgreSQL extensions and tools.
    • Google Cloud Spanner also supports SQL for querying data, but it has some limitations compared to Citus. For example, it does not support all PostgreSQL extensions, and some complex queries may need to be rewritten to work with Spanner.
  5. Managed Service:

    • Citus can be run as a managed service on the Citus Cloud, which simplifies deployment and management of the database. It offers automated backups, scaling, and monitoring.
    • Google Cloud Spanner is a fully managed service provided by Google Cloud. It handles database administration tasks such as replication, backups, and scaling automatically, allowing users to focus on developing their applications.
  6. Pricing Model:

    • Citus is an open-source software that can be self-hosted or run on Citus Cloud, which offers different pricing tiers based on the number of nodes and storage required.
    • Google Cloud Spanner has a pay-as-you-go pricing model, where users are charged based on the amount of storage, compute, and network resources they consume. It offers different pricing tiers for different levels of performance and availability.

In summary, Citus and Google Cloud Spanner differ in their underlying data models, scalability approaches, consistency models, query languages, managed service offerings, and pricing models.

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Detailed Comparison

Citus
Citus
Google Cloud Spanner
Google Cloud Spanner

It's an extension to Postgres that distributes data and queries in a cluster of multiple machines. Its query engine parallelizes incoming SQL queries across these servers to enable human real-time (less than a second) responses on large datasets.

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.

Multi-Node Scalable PostgreSQL;Built-in Replication and High Availability;Real-time Reads/Writes On Multiple Nodes;Multi-core Parallel Processing of Queries;Tenant isolation
Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars
12.0K
GitHub Stars
2.0K
GitHub Forks
736
GitHub Forks
1.1K
Stacks
60
Stacks
57
Followers
124
Followers
117
Votes
11
Votes
3
Pros & Cons
Pros
  • 6
    Multi-core Parallel Processing
  • 3
    Drop-in PostgreSQL replacement
  • 2
    Distributed with Auto-Sharding
Pros
  • 1
    Scalable
  • 1
    Horizontal scaling
  • 1
    Strongly consistent
Integrations
.NET
.NET
Apache Spark
Apache Spark
Loggly
Loggly
Java
Java
Rails
Rails
Datadog
Datadog
Logentries
Logentries
Heroku
Heroku
Papertrail
Papertrail
PostgreSQL
PostgreSQL
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB
MongoDB
SQLite
SQLite

What are some alternatives to Citus, Google Cloud Spanner?

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.

Cassandra

Cassandra

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.

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.

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