DBMS > Alibaba Cloud MaxCompute vs. Badger vs. FileMaker vs. Hive

System Properties Comparison Alibaba Cloud MaxCompute vs. Badger vs. FileMaker vs. Hive

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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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

Primary database model

Relational DBMS

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

Key-value store

Relational DBMS

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

Score	0.78
Rank	#221	Overall
	#102	Relational DBMS

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

github.com/dgraph-io/badger

www.claris.com/filemaker

hive.apache.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

godoc.org/github.com/dgraph-io/badger

www.claris.com/resources/documentation

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

Developer

Alibaba

DGraph Labs

Claris

a subsidiary of Apple

Apache Software Foundation

initially developed by Facebook

Initial release

2016

2017

1983

2012

Current release

19.4.1, November 2021

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

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

Java

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

iOS

client part only
Linux
OS X
Windows

All OS with a Java VM

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

via plugins

SQL-like DML and DDL statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
Thrift

Supported programming languages

Java

PHP

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication, warm standby

since Version 14

selectable replication factor

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

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

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.

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

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