DBMS > Alibaba Cloud MaxCompute vs. EJDB vs. Faircom DB vs. Hawkular Metrics vs. MarkLogic

System Properties Comparison Alibaba Cloud MaxCompute vs. EJDB vs. Faircom DB vs. Hawkular Metrics vs. MarkLogic

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Operational and transactional Enterprise NoSQL database

Primary database model

Relational DBMS

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

Document store

Key-value store
Relational DBMS

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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

Score	0.78
Rank	#221	Overall
	#102	Relational DBMS

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	6.50
Rank	#56	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#5	Search engines

Website

www.alibabacloud.com/product/maxcompute

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-db

www.hawkular.org

www.marklogic.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

github.com/Softmotions/ejdb/blob/master/README.md

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

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.marklogic.com

Developer

Alibaba

Softmotions

FairCom Corporation

Community supported by Red Hat

MarkLogic Corp.

Initial release

2016

2012

1979

2014

2001

Current release

V12, November 2020

11.0, December 2022

License

Commercial or Open Source

commercial

Open Source

GPLv2

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

restricted free version is 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

ANSI C, C++

Java

C++

Server operating systems

hosted

server-less

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

easily portable to other OSs

Linux
OS X
Windows

Data scheme

yes

schema-free

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

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes, ANSI SQL with proprietary extensions

yes

SQL92

APIs and other access methods

Fluentd
Flume
MaxCompute Console

in-process shared library

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

HTTP REST

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Go
Java
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

yes

via XQuery or JavaScript

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

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

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

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

yes, with Range Indexes

User concepts

Access control

Access rights for users and roles

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

Role-based access control at the document and subdocument levels

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