DBMS > Amazon Aurora vs. Coveo vs. Dgraph vs. IBM Db2 Event Store vs. MonetDB

System Properties Comparison Amazon Aurora vs. Coveo vs. Dgraph vs. IBM Db2 Event Store vs. MonetDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Distributed and scalable native Graph DBMS

Distributed Event Store optimized for Internet of Things use cases

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Search engine

Graph DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	7.84
Rank	#44	Overall
	#28	Relational DBMS

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.coveo.com

dgraph.io

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

www.monetdb.org

Technical documentation

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

docs.coveo.com

dgraph.io/docs

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

www.monetdb.org/Documentation

Developer

Amazon

Coveo

Dgraph Labs, Inc.

IBM

MonetDB BV

Initial release

2015

2012

2016

2017

2004

Current release

2.0

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Mozilla Public License 2.0

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 C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

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

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

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

C#
Java
JavaScript
Python

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

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

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

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Sharding

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Synchronous replication via Raft

Active-active shard replication

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

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

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

fine grained access rights according to SQL-standard

granular access controls, API key management, content filters

Planned for future releases

fine grained access rights according to SQL-standard

More information provided by the system vendor

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