DBMS > Amazon DynamoDB vs. HarperDB vs. LevelDB vs. RDF4J vs. Sequoiadb

System Properties Comparison Amazon DynamoDB vs. HarperDB vs. LevelDB vs. RDF4J vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Key-value store

Document store

Key-value store

RDF store

Document store
Relational DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	0.55
Rank	#252	Overall
	#38	Document stores

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Website

aws.amazon.com/dynamodb

www.harperdb.io

github.com/google/leveldb

rdf4j.org

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.harperdb.io/docs

github.com/google/leveldb/blob/main/doc/index.md

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon

HarperDB

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Sequoiadb Ltd.

Initial release

2012

2017

2011

2004

2013

Current release

3.1, August 2021

1.23, February 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Node.js

C++

Java

C++

Server operating systems

hosted

Linux
OS X

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

dynamic schema

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

oid, date, timestamp, binary, regex

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-like data manipulation statements

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

none

Source-replica replication

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

Eventual Consistency

Foreign keys

Referential integrity

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

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

with automatic compression on writes

yes

in-memory storage is supported as well

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)

Access rights for users and roles

simple password-based access control

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