DBMS > Amazon SimpleDB vs. Apache IoTDB vs. STSdb vs. Tarantool

System Properties Comparison Amazon SimpleDB vs. Apache IoTDB vs. STSdb vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Key-value store

Time Series DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.88
Rank	#139	Overall
	#24	Key-value stores

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	1.67
Rank	#150	Overall
	#25	Document stores
	#25	Key-value stores
	#69	Relational DBMS

Website

aws.amazon.com/simpledb

iotdb.apache.org

github.com/STSSoft/STSdb4

www.tarantool.io

Technical documentation

docs.aws.amazon.com/simpledb

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

www.tarantool.io/en/doc

Developer

Amazon

Apache Software Foundation

STS Soft SC

Initial release

2007

2018

2011

2008

Current release

1.1.0, April 2023

4.0.8, September 2015

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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 and C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Windows

BSD
Linux
macOS

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

RESTful HTTP API

JDBC
Native API

.NET Client API

Open binary protocol

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

C#
Java

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

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

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Strong Consistency with Raft

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

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

yes

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

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Recent citations in the news

Amazon SimpleDB Management in Eclipse | AWS News Blog
22 July 2009, AWS Blog

Hands-on Tutorial for Getting Started with Amazon SimpleDB
28 May 2010, Packt Hub

Amazon DynamoDB Serves Trillions Of Requests Per Month While Counterpart SimpleDB Is No Longer A Listed Product On AWS
12 November 2013, TechCrunch

Amazon Goes Back to the Future With 'NoSQL' Database
19 January 2012, WIRED

Bungee Connect Opens up and Adds Amazon SimpleDB Access | Amazon Web Services
22 February 2008, AWS Blog

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