DBMS > Amazon Neptune vs. Blueflood vs. Infobright vs. Milvus vs. Oracle Rdb

System Properties Comparison Amazon Neptune vs. Blueflood vs. Infobright vs. Milvus vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Scalable TimeSeries DBMS based on Cassandra

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Primary database model

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

aws.amazon.com/neptune

blueflood.io

ignitetech.com/softwarelibrary/infobrightdb

milvus.io

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

aws.amazon.com/neptune/developer-resources

github.com/rax-maas/blueflood/wiki

milvus.io/docs/overview.md

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Amazon

Rackspace

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2017

2013

2005

2019

1984

Current release

2.3.4, January 2024

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Java

C++, Go

Server operating systems

hosted

Linux
OS X

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

HP Open VMS

Data scheme

schema-free

predefined scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HTTP REST

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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

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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

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