DBMS > Graph Engine vs. Informix vs. Milvus vs. NSDb

System Properties Comparison Graph Engine vs. Informix vs. Milvus vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

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

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Vector DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	16.32
Rank	#35	Overall
	#21	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

www.graphengine.io

www.ibm.com/products/informix

milvus.io

nsdb.io

Technical documentation

www.graphengine.io/docs/manual

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

milvus.io/docs/overview.md

nsdb.io/Architecture

Developer

Microsoft

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Initial release

2010

1984

2019

2017

Current release

14.10.FC5, November 2020

2.4.4, May 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

free developer edition available

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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

.NET and C

C, C++ and Java

C++, Go

Java, Scala

Server operating systems

.NET

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

Vector, Numeric and String

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

C#
C++
F#
Visual Basic

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual 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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Using Apache Lucene

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authentication, authorization, and auditing controls

Role based access control and fine grained access rights

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.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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