DBMS > Amazon DynamoDB vs. Derby vs. DuckDB vs. GeoSpock

System Properties Comparison Amazon DynamoDB vs. Derby vs. DuckDB vs. GeoSpock

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Spatial and temporal data processing engine for extreme data scale

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Website

aws.amazon.com/dynamodb

db.apache.org/derby

duckdb.org

geospock.com

Technical documentation

docs.aws.amazon.com/dynamodb

db.apache.org/derby/manuals/index.html

duckdb.org/docs

Developer

Amazon

Apache Software Foundation

GeoSpock

Initial release

2012

1997

2018

Current release

10.17.1.0, November 2023

0.10, February 2024

2.0, September 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

Open Source

MIT License

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++

Java, Javascript

Server operating systems

hosted

All OS with a Java VM

server-less

hosted

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.

yes

Secondary indexes

yes

temporal, categorical

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

APIs and other access methods

RESTful HTTP API

JDBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

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)

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

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