DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Hazelcast vs. OrigoDB vs. TempoIQ

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Hazelcast vs. OrigoDB vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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

A widely adopted in-memory data grid

A fully ACID in-memory object graph database

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Wide column store

Document store
Key-value store

Key-value store

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

hazelcast.com

origodb.com

tempoiq.com (offline)

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

hazelcast.org/imdg/docs

origodb.com/docs

Developer

Alibaba

Amazon

Hazelcast

Robert Friberg et al

TempoIQ

Initial release

2016

2012

2008

2009

under the name LiveDB

2012

Current release

5.3.6, November 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; commercial licenses available

Open Source

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

Java

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

Data scheme

schema-free

yes

schema-free

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.

yes

the object must implement a serialization strategy

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP API

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP API

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

by integration with AWS Lambda

yes

Events

yes

Domain Events

yes

Realtime Alerts

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

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 selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

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

one or two-phase-commit; repeatable reads; read commited

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

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)

Role-based access control

Role based authorization

simple authentication-based access control

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