DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. Realm vs. Spark SQL vs. TDengine

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. Realm vs. Spark SQL vs. TDengine

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service for use with business intelligence tools

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Spark SQL is a component on top of 'Spark Core' for structured data processing

Time Series DBMS and big data platform

Primary database model

Secondary database models

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/redshift

realm.io

spark.apache.org/sql

github.com/taosdata/TDengine
tdengine.com

Technical documentation

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

docs.aws.amazon.com/redshift

realm.io/docs

spark.apache.org/docs/latest/sql-programming-guide.html

docs.tdengine.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon (based on PostgreSQL)

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

TDEngine, previously Taos Data

Initial release

2016

2012

2014

2019

Current release

3.5.0 ( 2.13), September 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

AGPL V3, also commercial editions available

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

Scala

Server operating systems

hosted

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Linux
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

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

in Python

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.