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

Google Cloud Spanner vs Memcached

OverviewComparisonAlternatives

Overview

Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
Google Cloud Spanner
Google Cloud Spanner
Stacks57
Followers117
Votes3
GitHub Stars2.0K
Forks1.1K

Google Cloud Spanner vs Memcached: What are the differences?

Google Cloud Spanner and Memcached are two popular data storage solutions with distinct characteristics. Google Cloud Spanner is a globally distributed, horizontally scalable relational database designed for high availability and consistency, while Memcached is an in-memory key-value store that is used for caching data to improve application performance. Below are key differences between Google Cloud Spanner and Memcached:

  1. Consistency Model: Google Cloud Spanner supports strong consistency, allowing for transactions with ACID properties across globally distributed data, while Memcached provides eventual consistency, which may lead to data staleness in distributed environments.

  2. Data Persistence: Google Cloud Spanner persists data on disk, ensuring durability even in the event of system failures, whereas Memcached stores data only in memory, requiring data to be recomputed or fetched from a persistent data store upon restarts.

  3. Query Language Support: Google Cloud Spanner offers SQL-like querying capabilities, making it familiar to developers and allowing complex queries to be executed directly on the database, while Memcached has no querying language and relies on simple get and set operations for data retrieval.

  4. Scalability: Google Cloud Spanner can horizontally scale both storage and compute resources to accommodate increasing workloads and data volumes, whereas Memcached's scalability is limited to the memory capacity of individual nodes, requiring sharding for distributed setups.

  5. Use Cases: Google Cloud Spanner is suited for mission-critical applications requiring high availability, strong consistency, and scalability across regions, such as financial services and e-commerce platforms, while Memcached is commonly used for caching transient data to reduce database load and response times in web applications.

In Summary, Google Cloud Spanner and Memcached differ in their consistency models, data persistence mechanisms, query language support, scalability options, and ideal use cases for various applications.

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Detailed Comparison

Memcached
Memcached
Google Cloud Spanner
Google Cloud Spanner

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.

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.

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Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars
14.0K
GitHub Stars
2.0K
GitHub Forks
3.3K
GitHub Forks
1.1K
Stacks
7.9K
Stacks
57
Followers
5.7K
Followers
117
Votes
473
Votes
3
Pros & Cons
Pros
  • 139
    Fast object cache
  • 129
    High-performance
  • 91
    Stable
  • 65
    Mature
  • 33
    Distributed caching system
Cons
  • 2
    Only caches simple types
Pros
  • 1
    Scalable
  • 1
    Horizontal scaling
  • 1
    Strongly consistent
Integrations
No integrations available
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB
MongoDB
SQLite
SQLite

What are some alternatives to Memcached, 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.

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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