DBMS > Alibaba Cloud MaxCompute vs. Faircom EDGE vs. Firebase Realtime Database vs. Ignite vs. SwayDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Faircom EDGE vs. Firebase Realtime Database vs. Ignite vs. SwayDB

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

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

Key-value store
Relational DBMS

Document store

Key-value store
Relational DBMS

Key-value store

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

www.faircom.com/products/faircom-edge

firebase.google.com/products/realtime-database

ignite.apache.org

swaydb.simer.au

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

firebase.google.com/docs/database

apacheignite.readme.io/docs

Developer

Alibaba

FairCom Corporation

Google

acquired by Google 2014

Apache Software Foundation

Simer Plaha

Initial release

2016

1979

2012

2015

2018

Current release

V3, October 2020

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

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

ANSI C, C++

C++, Java, .Net

Scala

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

ANSI SQL queries

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

Java

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Java
JavaScript
Objective-C

C#
C++
Java
PHP
Python
Ruby
Scala

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

Callbacks are triggered when data changes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

yes

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes, based on authentication and database rules

Security Hooks for custom implementations

More information provided by the system vendor

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More resources

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