DBMS > GeoMesa vs. OpenMLDB vs. RavenDB vs. WakandaDB

System Properties Comparison GeoMesa vs. OpenMLDB vs. RavenDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

An open-source machine learning database that provides a feature platform for training and inference

Open Source Operational and Transactional Enterprise NoSQL Document Database

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Relational DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

Technical documentation

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

openmldb.ai/docs/zh/main

ravendb.net/docs

wakanda.github.io/doc

Developer

CCRi and others

4 Paradigm Inc.

Hibernating Rhinos

Wakanda SAS

Initial release

2014

2020

2010

2012

Current release

5.0.0, May 2024

2024-2 February 2024

5.4, July 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL version 3, commercial license available

Open Source

AGPLv3, extended commercial license 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

C++, Java, Scala

C++, JavaScript

Server operating systems

Linux

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Windows

Data scheme

yes

Fixed schema

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

SQL-like query language (RQL)

APIs and other access methods

JDBC
SQLAlchemy

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C++
Go
Java
Python
Scala

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

Multi-source replication

none

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

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

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

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

yes

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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