DBMS > Amazon DynamoDB vs. EXASOL vs. IBM Db2 Event Store vs. RDF4J vs. RRDtool

System Properties Comparison Amazon DynamoDB vs. EXASOL vs. IBM Db2 Event Store vs. RDF4J vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Distributed Event Store optimized for Internet of Things use cases

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Document store
Key-value store

Relational DBMS

Event Store
Time Series DBMS

RDF store

Time Series DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.exasol.com

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

rdf4j.org

oss.oetiker.ch/rrdtool

Technical documentation

docs.aws.amazon.com/dynamodb

www.exasol.com/resources

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

rdf4j.org/documentation

oss.oetiker.ch/rrdtool/doc

Developer

Amazon

Exasol

IBM

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Tobias Oetiker

Initial release

2012

2000

2017

2004

1999

Current release

2.0

1.8.0, 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free developer edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V2 and FLOSS

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++

Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Unix
Windows

HP-UX
Linux

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

in-process shared library
Pipes

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
Lua
Python
R

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

Java
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

none

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

by using the rrdcached daemon

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 storage is supported as well

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 can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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