DBMS > Amazon Aurora vs. Amazon DynamoDB vs. Dgraph vs. Galaxybase vs. IBM Db2 Event Store

System Properties Comparison Amazon Aurora vs. Amazon DynamoDB vs. Dgraph vs. Galaxybase vs. IBM Db2 Event Store

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

Distributed and scalable native Graph DBMS

Scalable, ACID-compliant native distributed parallel graph platform

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Relational DBMS

Document store
Key-value store

Graph DBMS

Event Store
Time Series DBMS

Secondary database models

Document store

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

aws.amazon.com/rds/aurora

aws.amazon.com/dynamodb

dgraph.io

galaxybase.com

www.ibm.com/products/db2-event-store

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.aws.amazon.com/dynamodb

dgraph.io/docs

www.ibm.com/docs/en/db2-event-store

Developer

Amazon

Dgraph Labs, Inc.

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

IBM

Initial release

2015

2012

2016

2017

Current release

Nov 20, November 2021

2.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

free developer edition 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 and Java

C and C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Data scheme

yes

schema-free

Strong typed schema

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Go
Java
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

yes

user defined procedures and functions

yes

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Synchronous replication via Raft

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

No - written data is immutable

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

In-memory capabilities

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

yes

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)

Planned for future releases

Role-based access control

fine grained access rights according to SQL-standard

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