DBMS > Google Cloud Datastore vs. Memcached vs. Redis

System Properties Comparison Google Cloud Datastore vs. Memcached vs. Redis

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

In-memory key-value store, originally intended for caching

In-memory data structure store, used as database, cache and message broker

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Document store

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Secondary database models

Document store

with Redis Modules
Graph DBMS

with Redis Modules
Spatial DBMS
Search engine

with Redis Modules
Time Series DBMS

with Redis Modules

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.02
Rank	#80	Overall
	#12	Document stores

Score	24.50
Rank	#30	Overall
	#4	Key-value stores

Score	162.17
Rank	#7	Overall
	#1	Key-value stores

Website

cloud.google.com/datastore

www.memcached.org

redis.io

Technical documentation

cloud.google.com/datastore/docs

github.com/memcached/memcached/wiki

redis.io/documentation

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Salvatore Sanfilippo

Development sponsored by Redis Labs

Initial release

2008

2003

2009

Current release

1.6.9, November 2020

6.2.1 , March 2021

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

BSD 3-Clause, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

ScaleGrid for Redis: Fully managed hosting for Redis on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
Redis Enterprise Cloud: Instantly scale and pay only for the resources you need - on any cloud - AWS, Azure or Google Cloud.

Implementation language

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

Typing

predefined data types such as float or date

yes, details here

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language (GQL)

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Proprietary protocol

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

using Google App Engine

Lua

Triggers

Callbacks using the Google Apps Engine

publish/subscribe channels provide limited trigger functionality

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

Simple password-based access control

Access control lists and SSL are available in the commercial version

More information provided by the system vendor

Specific characteristics

Redis, benchmarked as the world's fastest database, reduces application complexity,...
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Competitive advantages

Redis is an in-memory database platform offering native support of wide range of...
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Typical application scenarios

Redis powers personalization, real-time fraud detection, IoT, e-commerce, real-time...
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Key customers

Verizon, Vodafone, Atlassian, Trip Advisor, Jet.com, Nokia, Samsung, HTC, Docker,...
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Licensing and pricing models

The licensing model is subscription based. Redis Enterprise Cloud is priced according...
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