DBMS > Alibaba Cloud MaxCompute vs. FileMaker vs. Google BigQuery vs. Prometheus vs. Riak KV

System Properties Comparison Alibaba Cloud MaxCompute vs. FileMaker vs. Google BigQuery vs. Prometheus vs. Riak KV

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.

Large scale data warehouse service with append-only tables

Open-source Time Series DBMS and monitoring system

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

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

Relational DBMS

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

www.claris.com/filemaker

cloud.google.com/bigquery

prometheus.io

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

prometheus.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Alibaba

Claris

a subsidiary of Apple

Google

OpenSource, formerly Basho Technologies

Initial release

2016

1983

2010

2015

2009

Current release

19.4.1, November 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

hosted

Linux
Windows

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language

yes

via plugins

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

Java

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions

in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

no "single point of failure"

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

yes

by Federation

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

Since BigQuery is designed for querying 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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes, using Riak Security

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