DBMS > GeoMesa vs. ToroDB vs. VictoriaMetrics vs. Vitess

System Properties Comparison GeoMesa vs. ToroDB vs. VictoriaMetrics vs. Vitess

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	1.23
Rank	#165	Overall
	#15	Time Series DBMS

Score	0.86
Rank	#202	Overall
	#95	Relational DBMS

Website

www.geomesa.org

github.com/torodb/server

victoriametrics.com

vitess.io

Technical documentation

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

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

vitess.io/docs

Developer

CCRi and others

8Kdata

VictoriaMetrics

The Linux Foundation, PlanetScale

Initial release

2014

2016

2018

2013

Current release

5.0.1, July 2024

v1.91, May 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL-V3

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0, commercial licenses 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

All OS with a Java 7 VM

FreeBSD
Linux
macOS
OpenBSD

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

with proprietary extensions

APIs and other access methods

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

Synchronous replication

Multi-source replication
Source-replica replication

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
Immediate Consistency

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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