DBMS > Amazon DocumentDB vs. Blueflood vs. Snowflake vs. YTsaurus

System Properties Comparison Amazon DocumentDB vs. Blueflood vs. Snowflake vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Scalable TimeSeries DBMS based on Cassandra

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

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store

Time Series DBMS

Relational DBMS

Document store
Key-value store

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.15
Rank	#323	Overall
	#44	Document stores
	#47	Key-value stores

Website

aws.amazon.com/documentdb

blueflood.io

www.snowflake.com

ytsaurus.tech

Technical documentation

aws.amazon.com/documentdb/resources

github.com/rax-maas/blueflood/wiki

docs.snowflake.net/manuals/index.html

ytsaurus.tech/docs/en

Developer

Rackspace

Snowflake Computing Inc.

Yandex

Initial release

2019

2013

2014

2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X

hosted

Ubuntu

Data scheme

schema-free

predefined scheme

yes

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

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

YQL, an SQL-based language, is supported

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

JavaScript (Node.js)
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

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.

User concepts

Access control

Access rights for users and roles

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

Access Control Lists

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