DBMS > Amazon DocumentDB vs. Geode vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

System Properties Comparison Amazon DocumentDB vs. Geode vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Cloud-based data warehousing service

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store

Key-value store

Relational DBMS

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	1.99
Rank	#133	Overall
	#23	Key-value stores

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

aws.amazon.com/documentdb

geode.apache.org

www.ibm.com/products/db2/warehouse

www.snowflake.com

sqream.com

Technical documentation

aws.amazon.com/documentdb/resources

geode.apache.org/docs

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

IBM

Snowflake Computing Inc.

SQream Technologies

Initial release

2019

2002

2014

2017

Current release

1.1, February 2017

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java Client API
Memcached protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
All JVM based languages
C++
Groovy
Java
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

PL/SQL, SQL PL

user defined functions

user defined functions in Python

Triggers

yes

Cache Event Listeners

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

yes

none

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

Eventual Consistency

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

yes, on a single node

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

Access rights per client and object definable

fine grained access rights according to SQL-standard

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

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