DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. EsgynDB vs. FileMaker vs. Google BigQuery vs. SiteWhere

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. EsgynDB vs. FileMaker vs. Google BigQuery vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Large scale data warehouse service with append-only tables

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Time Series DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.esgyn.cn

www.claris.com/filemaker

cloud.google.com/bigquery

github.com/sitewhere/sitewhere

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

sitewhere1.sitewhere.io/index.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Esgyn

Claris

a subsidiary of Apple

Google

SiteWhere

Initial release

2016

2015

1983

2010

Current release

19.4.1, November 2021

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

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

Java

Server operating systems

hosted

Linux

iOS

client part only
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

predefined scheme

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

yes

via plugins

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC/ADO.Net

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication between multi datacenters

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

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)

Users with fine-grained authorization concept

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