DBMS > Amazon DynamoDB vs. Drizzle vs. H2 vs. Hive

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. H2 vs. Hive

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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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

Spatial 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	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

aws.amazon.com/dynamodb

www.h2database.com

hive.apache.org

Technical documentation

docs.aws.amazon.com/dynamodb

www.h2database.com/html/main.html

cwiki.apache.org/confluence/display/Hive/Home

Developer

Amazon

Drizzle project, originally started by Brian Aker

Thomas Mueller

Apache Software Foundation

initially developed by Facebook

Initial release

2012

2008

2005

2012

Current release

7.2.4, September 2012

2.2.220, July 2023

3.1.3, April 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC

JDBC
ODBC

JDBC
ODBC
Thrift

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Java
PHP

Java

C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

user defined functions and integration of map-reduce

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual 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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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