DBMS > Alibaba Cloud MaxCompute vs. Bangdb vs. Faircom DB vs. Hazelcast

System Properties Comparison Alibaba Cloud MaxCompute vs. Bangdb vs. Faircom DB vs. Hazelcast

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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

Converged and high performance database for device data, events, time series, document and graph

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A widely adopted in-memory data grid

Primary database model

Relational DBMS

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

Document store
Graph DBMS
Time Series DBMS

Key-value store
Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Document store

JSON support with IMDG 3.12

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

bangdb.com

www.faircom.com/products/faircom-db

hazelcast.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.bangdb.com

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

hazelcast.org/imdg/docs

Developer

Alibaba

Sachin Sinha, BangDB

FairCom Corporation

Hazelcast

Initial release

2016

2012

1979

2008

Current release

BangDB 2.0, October 2021

V12, November 2020

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Restricted, free version available

Open Source

Apache Version 2; commercial licenses 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.

Implementation language

C, C++

ANSI C, C++

Java

Server operating systems

hosted

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

All OS with a Java VM

Data scheme

yes

schema-free

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes, ANSI SQL Types, JSON, typed binary structures

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

the object must implement a serialization strategy

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL-like query language

SQL like support with command line tool

yes, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Proprietary protocol
RESTful HTTP API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

Java

C
C#
C++
Java
Python

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

yes

Event Listeners, Executor Services

Triggers

yes, Notifications (with Streaming only)

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor, Knob for CAP (enterprise version only)

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Fine grained access rights according to SQL-standard with additional protections for files

Role-based access control

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