DBMS > Amazon DynamoDB vs. GraphDB vs. LokiJS vs. Vitess

System Properties Comparison Amazon DynamoDB vs. GraphDB vs. LokiJS vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

In-memory JavaScript DBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Key-value store

Graph DBMS
RDF store

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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	2.76
Rank	#99	Overall
	#8	Graph DBMS
	#4	RDF stores

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	0.86
Rank	#202	Overall
	#95	Relational DBMS

Website

aws.amazon.com/dynamodb

www.ontotext.com

github.com/techfort/LokiJS

vitess.io

Technical documentation

docs.aws.amazon.com/dynamodb

graphdb.ontotext.com/documentation

techfort.github.io/LokiJS

vitess.io/docs

Social network pages

Developer

Amazon

Ontotext

The Linux Foundation, PlanetScale

Initial release

2012

2000

2014

2013

Current release

10.4, October 2023

15.0.2, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Apache Version 2.0, commercial licenses available

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

Java

JavaScript

Server operating systems

hosted

All OS with a Java VM
Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Docker
Linux
macOS

Data scheme

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

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

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

via views

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

JavaScript API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

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

none

Multi-source replication
Source-replica replication

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

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

Constraint checking

yes

not for MyISAM storage engine

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

atomic operations within a single collection possible

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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)

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

Using Entity Linking to Turn Your Graph into a Knowledge Graph
23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.