DBMS > Brytlyt vs. GeoMesa vs. Milvus vs. NSDb vs. WakandaDB

System Properties Comparison Brytlyt vs. GeoMesa vs. Milvus vs. NSDb vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

docs.brytlyt.io

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

milvus.io/docs/overview.md

nsdb.io/Architecture

wakanda.github.io/doc

Developer

Brytlyt

CCRi and others

Wakanda SAS

Initial release

2016

2014

2019

2017

2012

Current release

5.0, August 2023

4.0.5, February 2024

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

Open Source

Apache Version 2.0

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

C, C++ and CUDA

Scala

C++, Go

Java, Scala

C++, JavaScript

Server operating systems

Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes: int, bigint, decimal, 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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

Java
Scala

JavaScript

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

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

Source-replica replication

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Using Apache Lucene

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

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

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

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

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

London data analytics startup Brytlyt raises €4.43M from Amsterdam-based Finch Capital, others
22 December 2021, Silicon Canals

Brytlyt Secures $4M in Series A Funding
20 May 2020, Datanami

Brytlyt becomes NVIDIA Inception Premier Partner
31 January 2023, PR Newswire

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

provided by Google News

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Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Cloud boosts vector database performance
31 January 2024, InfoWorld

provided by Google News

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