DBMS > Amazon Redshift vs. Firebird vs. HarperDB vs. Milvus

System Properties Comparison Amazon Redshift vs. Firebird vs. HarperDB vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Firebird is an open source RDBMS forked from Borland's InterBase

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

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

Primary database model

Relational DBMS

Document store

Vector DBMS

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

Score	14.07
Rank	#38	Overall
	#23	Relational DBMS

Score	18.43
Rank	#30	Overall
	#18	Relational DBMS

Score	0.55
Rank	#240	Overall
	#38	Document stores

Score	2.85
Rank	#95	Overall
	#5	Vector DBMS

Website

aws.amazon.com/redshift

www.firebirdsql.org

www.harperdb.io

milvus.io

Technical documentation

docs.aws.amazon.com/redshift

www.firebirdsql.org/en/reference-manuals

docs.harperdb.io/docs

milvus.io/docs/overview.md

Developer

Amazon (based on PostgreSQL)

Firebird Foundation

HarperDB

Initial release

2012

2000

As fork of Borland's InterBase

2017

2019

Current release

5.0.1, August 2024

3.1, August 2021

2.4.4, May 2024

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

commercial

free community edition available

Open Source

Apache Version 2.0

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

C and C++

Node.js

C++, Go

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

dynamic schema

Typing

predefined data types such as float or date

yes

JSON data types

Vector, Numeric and 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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like data manipulation statements

APIs and other access methods

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Server-side scripts

Stored procedures

user defined functions

in Python

PSQL

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

the nodes on which a table resides can be defined

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Users with fine-grained authorization concept

Access rights for users and roles

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...
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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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