DBMS > Amazon DynamoDB vs. Amazon SimpleDB vs. Badger vs. Qdrant

System Properties Comparison Amazon DynamoDB vs. Amazon SimpleDB vs. Badger vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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 embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A high-performance vector database with neural network or semantic-based matching

Primary database model

Document store
Key-value store

Key-value store

Vector DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

aws.amazon.com/dynamodb

aws.amazon.com/simpledb

github.com/dgraph-io/badger

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.aws.amazon.com/dynamodb

docs.aws.amazon.com/simpledb

godoc.org/github.com/dgraph-io/badger

qdrant.tech/documentation

Developer

Amazon

DGraph Labs

Qdrant

Initial release

2012

2007

2017

2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

BSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Concurrent data updates can be detected by the application

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

Key-based authentication

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