DBMS > Amazon DocumentDB vs. SAP HANA vs. Snowflake vs. SWC-DB

System Properties Comparison Amazon DocumentDB vs. SAP HANA vs. Snowflake vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

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

In-memory, column based data store. Available as appliance or cloud service

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

A high performance, scalable Wide Column DBMS

Primary database model

Document store

Relational DBMS

Wide column store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Time Series DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

aws.amazon.com/documentdb

www.sap.com/products/hana.html

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

aws.amazon.com/documentdb/resources

help.sap.com/hana

docs.snowflake.net/manuals/index.html

Developer

SAP

Snowflake Computing Inc.

Alex Kashirin

Initial release

2019

2010

2014

2020

Current release

2.0 SPS07 (April 4, 2023), April 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Appliance or cloud-service

hosted

Linux

Data scheme

schema-free

yes

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

schema-free

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

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

SQLScript, R

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

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

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

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.

yes

User concepts

Access control

Access rights for users and roles

yes

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

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