DBMS > AgensGraph vs. Amazon DynamoDB vs. Kinetica vs. MarkLogic

System Properties Comparison AgensGraph vs. Amazon DynamoDB vs. Kinetica vs. MarkLogic

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Fully vectorized database across both GPUs and CPUs

Operational and transactional Enterprise NoSQL database

Primary database model

Graph DBMS
Relational DBMS

Document store
Key-value store

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Website

bitnine.net/agensgraph

aws.amazon.com/dynamodb

www.kinetica.com

www.progress.com/marklogic

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/dynamodb

docs.kinetica.com

www.progress.com/marklogic/documentation

Developer

Bitnine Global Inc.

Amazon

Kinetica

MarkLogic Corp.

Initial release

2016

2012

2001

Current release

2.1, December 2018

7.1, August 2021

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free tier for a limited amount of database operations

commercial

restricted free version is 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

C, C++

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

depending on used data model

schema-free

yes

schema-free

Schema can be enforced

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL92

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

C
Java
JavaScript
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

via XQuery or JavaScript

Triggers

yes

by integration with AWS Lambda

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

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

can act as a resource manager in an XA/JTA transaction

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.

yes

GPU vRAM or System RAM

yes, with Range Indexes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles on table level

Role-based access control at the document and subdocument levels

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