DBMS > GeoMesa vs. Machbase Neo vs. Milvus vs. STSdb vs. WakandaDB

System Properties Comparison GeoMesa vs. Machbase Neo vs. Milvus vs. STSdb vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

TimeSeries DBMS for AIoT and BigData

A DBMS designed for efficient storage of vector data and vector similarity searches

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.geomesa.org

machbase.com

milvus.io

github.com/STSSoft/STSdb4

wakanda.github.io

Technical documentation

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

machbase.com/dbms

milvus.io/docs/overview.md

wakanda.github.io/doc

Developer

CCRi and others

Machbase

STS Soft SC

Wakanda SAS

Initial release

2014

2013

2019

2011

2012

Current release

4.0.5, February 2024

V8.0, August 2023

2.3.4, January 2024

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free test version available

Open Source

Apache Version 2.0

Open Source

GPLv2, 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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Scala

C++, Go

C++, JavaScript

Server operating systems

Linux
macOS
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

primitive types and user defined types (classes)

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

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

RESTful HTTP API

.NET Client API

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C++
Go
Java
JavaScript (Node.js)
Python

C#
Java

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor

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

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

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

yes

User concepts

Access control

yes

depending on the DBMS used for storage

simple password-based access control

Role based access control and fine grained access rights

yes

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Vector databases
2 June 2023, Matthias Gelbmann

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