DBMS > AgensGraph vs. Amazon DynamoDB vs. Memcached vs. Vertica

System Properties Comparison AgensGraph vs. Amazon DynamoDB vs. Memcached vs. Vertica

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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

In-memory key-value store, originally intended for caching

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

Graph DBMS
Relational DBMS

Document store
Key-value store

Key-value store

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	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

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

Score	16.84
Rank	#32	Overall
	#4	Key-value stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/dynamodb

www.memcached.org

www.vertica.com

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/dynamodb

github.com/memcached/memcached/wiki

vertica.com/documentation

Developer

Bitnine Global Inc.

Amazon

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2012

2003

2005

Current release

2.1, December 2018

1.6.29, June 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free tier for a limited amount of database operations

Open Source

BSD license

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

C++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

depending on used data model

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

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

SQL

Support of SQL

yes

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

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

Proprietary protocol

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

character-based, interactive, front-end utility

Supported programming languages

C
Java
JavaScript
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by integration with AWS Lambda

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Repcached, a Memcached patch, provides this functionallity

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)

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

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

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)

yes

using SASL (Simple Authentication and Security Layer) protocol

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

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