DBMS > EsgynDB vs. Hawkular Metrics vs. IBM Db2 Event Store

System Properties Comparison EsgynDB vs. Hawkular Metrics vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Primary database model

Relational DBMS

Time Series DBMS

Event Store
Time Series DBMS

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

www.esgyn.cn

www.hawkular.org

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

Technical documentation

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

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

Developer

Esgyn

Community supported by Red Hat

IBM

Initial release

2015

2014

2017

Current release

2.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free developer edition available

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

C++, Java

Java

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP REST

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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

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