DBMS > Amazon DynamoDB vs. Apache Drill vs. HyperSQL vs. Yanza

System Properties Comparison Amazon DynamoDB vs. Apache Drill vs. HyperSQL vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Time Series DBMS for IoT Applications

Primary database model

Document store
Key-value store

Document store
Relational DBMS

Relational DBMS

Time Series 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	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

aws.amazon.com/dynamodb

drill.apache.org

hsqldb.org

yanza.com

Technical documentation

docs.aws.amazon.com/dynamodb

drill.apache.org/docs

hsqldb.org/web/hsqlDocsFrame.html

Developer

Amazon

Apache Software Foundation

Yanza

Initial release

2012

2001

2015

Current release

1.20.3, January 2023

2.7.2, June 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

based on BSD license

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++

All languages supporting JDBC/ODBC
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

Java, SQL

Triggers

yes

by integration with AWS Lambda

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Depending on the underlying data source

fine grained access rights according to SQL-standard

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