DBMS > Amazon Redshift vs. Derby vs. Hawkular Metrics vs. IBM Db2 Event Store vs. TerminusDB

System Properties Comparison Amazon Redshift vs. Derby vs. Hawkular Metrics vs. IBM Db2 Event Store vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Distributed Event Store optimized for Internet of Things use cases

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Time Series DBMS

Event Store
Time Series DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

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

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/redshift

db.apache.org/derby

www.hawkular.org

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

terminusdb.com

Technical documentation

docs.aws.amazon.com/redshift

db.apache.org/derby/manuals/index.html

www.hawkular.org/hawkular-metrics/docs/user-guide

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

terminusdb.github.io/terminusdb/#

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Community supported by Red Hat

IBM

DataChemist Ltd.

Initial release

2012

1997

2014

2017

2018

Current release

10.17.1.0, November 2023

2.0

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

GPL V3

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

Java

C and C++

Prolog, Rust

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

yes

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

through the embedded Spark runtime

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

JDBC

HTTP REST

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

Java

Go
Java
Python
Ruby

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on Cassandra

Active-active shard replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

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 journaling

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

Role-based access control

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