DBMS > EventStoreDB vs. GeoMesa vs. Quasardb vs. Riak TS

System Properties Comparison EventStoreDB vs. GeoMesa vs. Quasardb vs. Riak TS

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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.

Distributed, high-performance timeseries database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Event Store

Spatial DBMS

Time Series DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.eventstore.com

www.geomesa.org

quasar.ai

Technical documentation

developers.eventstore.com

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

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Event Store Limited

CCRi and others

quasardb

Open Source, formerly Basho Technologies

Initial release

2012

2014

2009

2015

Current release

21.2, February 2021

5.0.0, May 2024

3.14.1, January 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

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

C++

Erlang

Server operating systems

Linux
Windows

BSD
Linux
OS X
Windows

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

restricted

SQL

Support of SQL

SQL-like query language

yes, limited

APIs and other access methods

HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication with selectable replication factor

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

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

Transient mode

User concepts

Access control

yes

depending on the DBMS used for storage

Cryptographically strong user authentication and audit trail

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