DBMS > Hawkular Metrics vs. IBM Db2 Event Store vs. Oracle Coherence vs. SwayDB

System Properties Comparison Hawkular Metrics vs. IBM Db2 Event Store vs. Oracle Coherence vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

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

Oracles in-memory data grid solution

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Key-value store

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

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

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

www.hawkular.org

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

www.oracle.com/java/coherence

swaydb.simer.au

Technical documentation

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

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

docs.oracle.com/en/middleware/standalone/coherence

Developer

Community supported by Red Hat

IBM

Oracle

Simer Plaha

Initial release

2014

2017

2007

2018

Current release

2.0

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free developer edition available

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Java

Scala

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

HTTP REST

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

Go
Java
Python
Ruby

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

.Net
C++
Java

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Active-active shard replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

Atomic execution of operations

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

optionally

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

authentification to access the cache via certificates or http basic authentication

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