DBMS > Amazon DynamoDB vs. Drizzle vs. EXASOL vs. Prometheus vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. EXASOL vs. Prometheus vs. Snowflake

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Open-source Time Series DBMS and monitoring system

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

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/dynamodb

www.exasol.com

prometheus.io

www.snowflake.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.exasol.com/resources

prometheus.io/docs

docs.snowflake.net/manuals/index.html

Developer

Amazon

Drizzle project, originally started by Brian Aker

Exasol

Snowflake Computing Inc.

Initial release

2012

2008

2000

2015

2014

Current release

7.2.4, September 2012

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

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

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
Windows

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

Numeric data only

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.

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP API

JDBC

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Java
PHP

Java
Lua
Python
R

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

none

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

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 can be defined via the AWS Identity and Access Management (IAM)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles according to SQL-standard

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

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