DBMS > Amazon SimpleDB vs. atoti vs. Kdb vs. RethinkDB vs. SQLite

System Properties Comparison Amazon SimpleDB vs. atoti vs. Kdb vs. RethinkDB vs. SQLite

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

High performance Time Series DBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Object oriented DBMS

Time Series DBMS
Vector DBMS

Document store

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/simpledb

Technical documentation

docs.aws.amazon.com/simpledb

docs.atoti.io

code.kx.com

rethinkdb.com/docs

www.sqlite.org/docs.html

Developer

Amazon

ActiveViam

Kx Systems, a division of First Derivatives plc

The Linux Foundation

since July 2017

Dwayne Richard Hipp

Initial release

2007

2000

kdb was released 2000, kdb+ in 2003

2009

2000

Current release

3.6, May 2018

2.4.1, August 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free versions available

commercial

free 32-bit version

Open Source

Apache Version 2

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++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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.

yes

Secondary indexes

yes

All columns are indexed automatically

yes

table attribute 'grouped'

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (q)

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

user defined functions

Triggers

yes

with views

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding, horizontal partitioning

horizontal partitioning

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC based

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)

rights management via user accounts

yes

users and table-level permissions

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.