DBMS > IBM Db2 warehouse vs. LokiJS vs. Milvus vs. Ultipa vs. UniData,UniVerse

System Properties Comparison IBM Db2 warehouse vs. LokiJS vs. Milvus vs. Ultipa vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

In-memory JavaScript DBMS

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

High performance Graph DBMS supporting HTAP high availability cluster deployment

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

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

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

www.ibm.com/products/db2/warehouse

github.com/techfort/LokiJS

milvus.io

www.ultipa.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

techfort.github.io/LokiJS

milvus.io/docs/overview.md

www.ultipa.com/document

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

IBM

Ultipa

Rocket Software

Initial release

2014

2019

1985

Current release

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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

JavaScript

C++, Go

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

optional

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.

Import/export of XML data possible

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

JavaScript API

RESTful HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

PL/SQL, SQL PL

View functions in JavaScript

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Access rights according to SQL-standard and operating system based

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

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Vector databases
2 June 2023, Matthias Gelbmann

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