DBMS > FatDB vs. GeoMesa vs. HarperDB vs. Milvus vs. WakandaDB

System Properties Comparison FatDB vs. GeoMesa vs. HarperDB vs. Milvus vs. WakandaDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

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

Primary database model

Document store
Key-value store

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

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

docs.harperdb.io/docs

milvus.io/docs/overview.md

wakanda.github.io/doc

Developer

FatCloud

CCRi and others

HarperDB

Wakanda SAS

Initial release

2012

2014

2017

2019

2012

Current release

4.0.5, February 2024

3.1, August 2021

2.3.4, January 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

free community edition available

Open Source

Apache Version 2.0

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

Node.js

C++, Go

C++, JavaScript

Server operating systems

Windows

Linux
OS X

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

Via inetgration in SQL Server

SQL-like data manipulation statements

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

JavaScript

Server-side scripts

Stored procedures

yes

via applications

Custom Functions

since release 3.1

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

depending on storage layer

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on storage layer

Immediate Consistency

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Can implement custom security layer via applications

yes

depending on the DBMS used for storage

Access rights for users and roles

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

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