DBMS > Crux vs. Google Cloud Firestore vs. Redis

System Properties Comparison Crux vs. Google Cloud Firestore vs. Redis

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Editorial information provided by DB-Engines

Name

Description

Crux is a general purpose database with bitemporal SQL and Datalog and graph queries

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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
Search engine

with Redis Modules
Time Series DBMS

with Redis Modules

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

Score	0.00
Rank	#335	Overall
	#47	Document stores

Score	8.21
Rank	#51	Overall
	#9	Document stores

Score	155.01
Rank	#7	Overall
	#1	Key-value stores

Website

github.com/juxt/crux
opencrux.com

firebase.google.com/products/firestore

redis.io

Technical documentation

opencrux.com/reference/installation.html

firebase.google.com/docs/firestore

redis.io/documentation

Developer

Juxt Ltd.

Google

Salvatore Sanfilippo

Development sponsored by Redis Labs

Initial release

2019

2017

2009

Current release

1.12.1, September 2020

6.0.10 , January 2021

License

Commercial or Open Source

Open Source

MIT License

commercial

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.

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Redis Enterprise Cloud: Fully managed cloud service by the makers of Redis.

Implementation language

Clojure

Server operating systems

All OS with a Java 8 (and higher) VM
Linux

hosted

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, extensible-data-notation format

yes

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

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST
JDBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Clojure
Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

yes, Firebase Rules & Cloud Functions

Lua

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, each node contains all data

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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. Security Rules for 3rd party authentication using Firebase Auth.

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

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Competitive advantages

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Typical application scenarios

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Key customers

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Licensing and pricing models

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