DBMS > GeoMesa vs. JanusGraph vs. Milvus vs. Netezza vs. WakandaDB

System Properties Comparison GeoMesa vs. JanusGraph vs. Milvus vs. Netezza vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Data warehouse and analytics appliance part of IBM PureSystems

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	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.geomesa.org

janusgraph.org

milvus.io

www.ibm.com/products/netezza

wakanda.github.io

Technical documentation

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

docs.janusgraph.org

milvus.io/docs/overview.md

wakanda.github.io/doc

Developer

CCRi and others

Linux Foundation; originally developed as Titan by Aurelius

IBM

Wakanda SAS

Initial release

2014

2017

2019

2000

2012

Current release

4.0.5, February 2024

0.6.3, February 2023

2.3.4, January 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

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

Java

C++, Go

C++, JavaScript

Server operating systems

Linux
OS X
Unix
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

included in appliance

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

Clojure
Java
Python

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

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency
Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Role based access control and fine grained access rights

Users with fine-grained authorization concept

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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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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