DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Apache IoTDB vs. OceanBase

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Apache IoTDB vs. OceanBase

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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 distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Wide column store

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Wide column store

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	1.66
Rank	#147	Overall
	#68	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

iotdb.apache.org

en.oceanbase.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

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

en.oceanbase.com/docs/oceanbase-database

Developer

Alibaba

Amazon

Apache Software Foundation

OceanBase

previously Alibaba and Ant Group

Initial release

2016

2012

2018

2010

Current release

1.1.0, April 2023

4.3.0, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Commercial license 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

Java

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC
Native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
Python
Scala

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

yes

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

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)

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

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

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Integration with Hadoop and Spark

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

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

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

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, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High Availability : The five IDCs across three sites disaster recovery solution sets...
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Key customers

OceanBase Database has helped over 400 customers across industries upgrade their...
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Market metrics

TPC-C No.1 Performance , achieved a result of 707.35 million tpmC in the TPC-C benchmark...
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Licensing and pricing models

Mulan PubL v2 license for open source community edition. Commercial license for enterprise...
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