DBMS > Amazon DocumentDB vs. AnzoGraph DB vs. KeyDB vs. MySQL

System Properties Comparison Amazon DocumentDB vs. AnzoGraph DB vs. KeyDB vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Widely used open source RDBMS

Primary database model

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

aws.amazon.com/documentdb

cambridgesemantics.com/anzograph

github.com/Snapchat/KeyDB
keydb.dev

www.mysql.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.keydb.dev

dev.mysql.com/doc

Developer

Cambridge Semantics

EQ Alpha Technology Ltd.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2019

2018

2019

1995

Current release

2.3, January 2021

8.4.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

BSD-3

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

C and C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C++
Java
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

user defined functions and aggregates

Lua

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication in MPP-Cluster

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)

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

not needed in graphs

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

Users with fine-grained authorization concept

no user groups or roles

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