DBMS > Amazon DynamoDB vs. atoti vs. KeyDB vs. Microsoft Azure Cosmos DB vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. atoti vs. KeyDB vs. Microsoft Azure Cosmos DB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Document store
Key-value store

Object oriented DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/dynamodb

atoti.io

github.com/Snapchat/KeyDB
keydb.dev

azure.microsoft.com/services/cosmos-db

www.snowflake.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.atoti.io

docs.keydb.dev

learn.microsoft.com/azure/cosmos-db

docs.snowflake.net/manuals/index.html

Developer

Amazon

ActiveViam

EQ Alpha Technology Ltd.

Microsoft

Snowflake Computing Inc.

Initial release

2012

2019

2014

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free versions available

Open Source

BSD-3

commercial

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

hosted

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

JSON types

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

by using the Redis Search module

yes

All properties auto-indexed by default

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Python

Lua

JavaScript

user defined functions

Triggers

yes

by integration with AWS Lambda

JavaScript

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Strong eventual consistency with CRDTs

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Optimistic locking, atomic execution of commands blocks and scripts

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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)

simple password-based access control and ACL

Access rights can be defined down to the item level

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

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