DBMS > Alibaba Cloud MaxCompute vs. FileMaker vs. Oracle Berkeley DB vs. Percona Server for MongoDB vs. Snowflake

System Properties Comparison Alibaba Cloud MaxCompute vs. FileMaker vs. Oracle Berkeley DB vs. Percona Server for MongoDB vs. Snowflake

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.

Widely used in-process key-value store

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

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

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Relational 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	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.claris.com/filemaker

www.oracle.com/database/technologies/related/berkeleydb.html

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.claris.com/resources/documentation

docs.oracle.com/cd/E17076_05/html/index.html

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Claris

a subsidiary of Apple

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Percona

Snowflake Computing Inc.

Initial release

2016

1983

1994

2015

2014

Current release

19.4.1, November 2021

18.1.40, May 2020

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

GPL Version 2

commercial

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, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

via plugins

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Filemaker WebDirect
JDBC
ODBC

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

Java

PHP

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

JavaScript

user defined functions

Triggers

yes

only for the SQL API

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

yes

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

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

via In-Memory Engine

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 and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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