DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Apache IoTDB vs. Percona Server for MongoDB vs. Postgres-XL

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Apache IoTDB vs. Percona Server for MongoDB vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Wide column store

Document store
Key-value store

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

iotdb.apache.org

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

www.postgres-xl.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

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

www.postgres-xl.org/documentation

Developer

Alibaba

Amazon

Apache Software Foundation

Percona

Initial release

2016

2012

2018

2015

2014

since 2012, originally named StormDB

Current release

1.1.0, April 2023

3.4.10-2.10, November 2017

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

GPL Version 2

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux

Linux
macOS

Data scheme

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC
Native API

proprietary protocol using JSON

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
Python
Scala

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

ACID across one or more tables within a single AWS account and region

ACID

MVCC

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 based on subaccounts and tokens

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

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