DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Dgraph vs. Firebase Realtime Database vs. Solr

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Dgraph vs. Firebase Realtime Database vs. Solr

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

Large scale data warehouse service for use with business intelligence tools

Distributed and scalable native Graph DBMS

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

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

Secondary database models

Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

dgraph.io

firebase.google.com/products/realtime-database

solr.apache.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

dgraph.io/docs

firebase.google.com/docs/database

solr.apache.org/resources.html

Developer

Alibaba

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

Google

acquired by Google 2014

Apache Software Foundation

Initial release

2016

2012

2016

2012

2006

Current release

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux
OS X
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

does not fully support an SQL-standard

Solr Parallel SQL Interface

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

Java

All languages supporting JDBC/ODBC

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
JavaScript
Objective-C

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

limited functionality with using 'rules'

Java plugins

Triggers

Callbacks are triggered when data changes

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Synchronous replication via Raft

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

yes

optimistic locking

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.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Planned for future releases

yes, based on authentication and database rules

yes

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