DBMS > Amazon SimpleDB vs. etcd vs. Realm vs. RisingWave vs. SQLite

System Properties Comparison Amazon SimpleDB vs. etcd vs. Realm vs. RisingWave 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

A distributed reliable key-value store

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Document store

Relational DBMS

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

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/simpledb

etcd.io
github.com/etcd-io/etcd

realm.io

www.risingwave.com/database

www.sqlite.org

Technical documentation

docs.aws.amazon.com/simpledb

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

realm.io/docs

docs.risingwave.com/docs/current/intro

www.sqlite.org/docs.html

Developer

Amazon

Realm, acquired by MongoDB in May 2019

RisingWave Labs

Dwayne Richard Hipp

Initial release

2007

2014

2022

2000

Current release

3.4, August 2019

1.2, September 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Rust

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

Android
Backend: server-less
iOS
Windows

Docker
Linux
macOS

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

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

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

gRPC
JSON over HTTP

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 (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

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

runs within the applications so server-side scripts are unnecessary

UDFs in Python or Java

Triggers

yes, watching key changes

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

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

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

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

In-Memory realm

yes

User concepts

Access control

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

yes

Users and Roles

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