DBMS > Amazon DynamoDB vs. Bangdb vs. Dragonfly vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. Bangdb vs. Dragonfly vs. Snowflake

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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

Converged and high performance database for device data, events, time series, document and graph

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

aws.amazon.com/dynamodb

bangdb.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.snowflake.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.bangdb.com

www.dragonflydb.io/docs

docs.snowflake.net/manuals/index.html

Developer

Amazon

Sachin Sinha, BangDB

DragonflyDB team and community contributors

Snowflake Computing Inc.

Initial release

2012

2023

2014

Current release

BangDB 2.0, October 2021

1.0, March 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD 3

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

scheme-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

strings, hashes, lists, sets, sorted sets, bit arrays

yes

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

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

RESTful HTTP API

Proprietary protocol
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

CLI Client
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
Python

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

yes

by integration with AWS Lambda

yes, Notifications (with Streaming only)

publish/subscribe channels provide some trigger functionality

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

yes

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

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

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

yes (enterprise version only)

Password-based authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

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