DBMS > EventStoreDB vs. GeoMesa vs. Hawkular Metrics vs. Machbase Neo

System Properties Comparison EventStoreDB vs. GeoMesa vs. Hawkular Metrics vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

TimeSeries DBMS for AIoT and BigData

Primary database model

Event Store

Spatial DBMS

Time Series DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Website

Technical documentation

developers.eventstore.com

www.geomesa.org/documentation/stable/user/index.html

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

machbase.com/dbms

Developer

Event Store Limited

CCRi and others

Community supported by Red Hat

Machbase

Initial release

2012

2014

2013

Current release

21.2, February 2021

5.0.0, May 2024

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

free test version 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

Scala

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

Linux
macOS
Windows

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

SQL-like query language

APIs and other access methods

HTTP REST

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

Go
Java
Python
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor

based on Cassandra

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

volatile and lookup table

User concepts

Access control

yes

depending on the DBMS used for storage

simple password-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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