DBMS > Alibaba Cloud MaxCompute vs. BigObject vs. Faircom EDGE vs. Google Cloud Bigtable vs. searchxml

System Properties Comparison Alibaba Cloud MaxCompute vs. BigObject vs. Faircom EDGE vs. Google Cloud Bigtable vs. searchxml

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

Analytic DBMS for real-time computations and queries

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

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

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Relational DBMS

Key-value store
Wide column store

Native XML DBMS
Search engine

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.alibabacloud.com/product/maxcompute

bigobject.io

www.faircom.com/products/faircom-edge

cloud.google.com/bigtable

www.searchxml.net/category/products

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.bigobject.io

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

cloud.google.com/bigtable/docs

www.searchxml.net/support/handouts

Developer

Alibaba

BigObject, Inc.

FairCom Corporation

Google

informationpartners gmbh

Initial release

2016

2015

1979

2015

Current release

V3, October 2020

1.0

License

Commercial or Open Source

commercial

free community edition available

commercial

Restricted, free version available

commercial

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++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Windows

Data scheme

yes

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

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

SQL-like DML and DDL statements

yes

ANSI SQL queries

APIs and other access methods

Fluentd
Flume
MaxCompute Console

fluentd
ODBC
RESTful HTTP API

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Java

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

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

in Java

Lua

yes

.Net, JavaScript, C/C++

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

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

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency
Tunable Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

when using SQL

Transaction concepts

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

ACID

Atomic single-row operations

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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.

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

Domain, group and role-based access control at the document level and for application services

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