DBMS > Amazon CloudSearch vs. Amazon DynamoDB vs. GraphDB vs. Riak TS vs. Vertica

System Properties Comparison Amazon CloudSearch vs. Amazon DynamoDB vs. GraphDB vs. Riak TS vs. Vertica

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Search engine

Document store
Key-value store

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

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

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/dynamodb

www.ontotext.com

www.vertica.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/dynamodb

graphdb.ontotext.com/documentation

www.tiot.jp/riak-docs/riak/ts/latest

vertica.com/documentation

Social network pages

Developer

Amazon

Ontotext

Open Source, formerly Basho Technologies

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2000

2015

2005

Current release

10.4, October 2023

3.0.0, September 2022

12.0.3, January 2023

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

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

C++

Server operating systems

hosted

All OS with a Java VM
Linux
OS X
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

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

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

all search fields are automatically indexed

yes

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

restricted

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

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

yes, limited

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP API

RESTful HTTP API

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

HTTP API
Native Erlang Interface

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

Erlang

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by integration with AWS Lambda

yes

pre-commit hooks and post-commit hooks

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Multi-source replication

selectable replication factor

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Bi-directional Spark integration

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)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

links between datasets can be stored

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

In-memory capabilities

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

User concepts

Access control

authentication via encrypted signatures

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.

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

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Market metrics

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Licensing and pricing models

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Cost-based models and subscription-based models are both available. One license is...
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