DBMS > Alibaba Cloud MaxCompute vs. Badger vs. Google Cloud Firestore vs. Riak KV

System Properties Comparison Alibaba Cloud MaxCompute vs. Badger vs. Google Cloud Firestore vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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.

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Key-value store

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

github.com/dgraph-io/badger

firebase.google.com/products/firestore

Technical documentation

www.alibabacloud.com/help/en/maxcompute

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/firestore

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Alibaba

DGraph Labs

Google

OpenSource, formerly Basho Technologies

Initial release

2016

2017

2009

Current release

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

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.

Implementation language

Erlang

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

restricted

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

HTTP API
Native Erlang Interface

Supported programming languages

Java

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Java

yes, Firebase Rules & Cloud Functions

Erlang

Triggers

yes, with Cloud Functions

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

yes, using Riak Security

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More resources

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