DBMS > Alibaba Cloud MaxCompute vs. FileMaker vs. Hive vs. Lovefield vs. MySQL

System Properties Comparison Alibaba Cloud MaxCompute vs. FileMaker vs. Hive vs. Lovefield vs. MySQL

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Primary database model

Relational DBMS

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

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.claris.com/filemaker

hive.apache.org

google.github.io/lovefield

www.mysql.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.claris.com/resources/documentation

cwiki.apache.org/confluence/display/Hive/Home

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

Developer

Alibaba

Claris

a subsidiary of Apple

Apache Software Foundation

initially developed by Facebook

Google

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

1983

2012

2014

1995

Current release

19.4.1, November 2021

3.1.3, April 2022

2.1.12, February 2017

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

JavaScript

C and C++

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

via plugins

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

PHP

C++
Java
PHP
Python

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication, warm standby

since Version 14

selectable replication factor

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users and roles

simple rights management via user accounts and connection to external directory services

Access rights for users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

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