DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Kinetica vs. OrigoDB vs. SiteWhere

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Kinetica vs. OrigoDB vs. SiteWhere

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

Fully vectorized database across both GPUs and CPUs

A fully ACID in-memory object graph database

M2M integration platform for persisting/querying time series data

Primary database model

Wide column store

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Spatial DBMS
Time Series 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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

www.kinetica.com

origodb.com

github.com/sitewhere/sitewhere

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

docs.kinetica.com

origodb.com/docs

sitewhere1.sitewhere.io/index.html

Developer

Alibaba

Amazon

Kinetica

Robert Friberg et al

SiteWhere

Initial release

2016

2012

2009

under the name LiveDB

2010

Current release

7.1, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

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, C++

Java

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP REST

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

by integration with AWS Lambda

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

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)

Access rights for users and roles on table level

Role based authorization

Users with fine-grained authorization concept

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