DBMS > 4D vs. Machbase Neo vs. Milvus vs. RRDtool vs. SQLite

System Properties Comparison 4D vs. Machbase Neo vs. Milvus vs. RRDtool vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

TimeSeries DBMS for AIoT and BigData

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.4d.com

machbase.com

milvus.io

oss.oetiker.ch/rrdtool

www.sqlite.org

Technical documentation

developer.4d.com

machbase.com/dbms

milvus.io/docs/overview.md

oss.oetiker.ch/rrdtool/doc

www.sqlite.org/docs.html

Developer

4D, Inc

Machbase

Tobias Oetiker

Dwayne Richard Hipp

Initial release

1984

2013

2019

1999

2000

Current release

v20, April 2023

V8.0, August 2023

2.3.4, January 2024

1.8.0, 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free test version available

Open Source

Apache Version 2.0

Open Source

GPL V2 and FLOSS

Open Source

Public Domain

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++, Go

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

OS X
Windows

Linux
macOS
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

HP-UX
Linux

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

in-process shared library
Pipes

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

none

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

none

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

by using the rrdcached daemon

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

Users and groups

simple password-based access control

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...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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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...
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