DBMS > Amazon DynamoDB vs. Prometheus vs. Sequoiadb vs. SQLite vs. Stardog

System Properties Comparison Amazon DynamoDB vs. Prometheus vs. Sequoiadb vs. SQLite vs. Stardog

Editorial information provided by DB-Engines

Name

Description

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

Open-source Time Series DBMS and monitoring system

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Key-value store

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Graph DBMS
RDF store

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

prometheus.io/docs

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

www.sqlite.org/docs.html

docs.stardog.com

Developer

Amazon

Sequoiadb Ltd.

Dwayne Richard Hipp

Stardog-Union

Initial release

2012

2015

2013

2000

2010

Current release

3.46.1 (13 August 2024), August 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Public Domain

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

hosted

Linux
Windows

Linux

server-less

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

Numeric data only

yes

oid, date, timestamp, binary, regex

yes

not rigid because of 'dynamic typing' concept.

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
C++
Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

by integration with AWS Lambda

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

Source-replica replication

none

Multi-source replication in HA-Cluster

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

none

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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)

simple password-based access control

Access rights for users and roles

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