DBMS > Amazon SimpleDB vs. atoti vs. IRONdb vs. RisingWave vs. SQLite

System Properties Comparison Amazon SimpleDB vs. atoti vs. IRONdb vs. RisingWave vs. SQLite

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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 in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/simpledb

atoti.io

www.circonus.com/solutions/time-series-database/

www.risingwave.com/database

www.sqlite.org

Technical documentation

docs.aws.amazon.com/simpledb

docs.atoti.io

docs.circonus.com/irondb/category/getting-started

docs.risingwave.com/docs/current/intro

www.sqlite.org/docs.html

Developer

Amazon

ActiveViam

Circonus LLC.

RisingWave Labs

Dwayne Richard Hipp

Initial release

2007

2017

2022

2000

Current release

V0.10.20, January 2018

1.2, September 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache Version 2.0

Open Source

Public Domain

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++

Rust

Server operating systems

hosted

Linux

Docker
Linux
macOS

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

text, numeric, histograms

Standard SQL-types and JSON

yes

not rigid because of 'dynamic typing' concept.

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

Multidimensional Expressions (MDX)

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

HTTP API

JDBC
PostgreSQL wire protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Go
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Python

yes, in Lua

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding, horizontal partitioning

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency per node, eventual consistency across nodes

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

Users and Roles

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