DBMS > Brytlyt vs. DolphinDB vs. Milvus vs. Oracle

System Properties Comparison Brytlyt vs. DolphinDB vs. Milvus vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

Widely used RDBMS

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

brytlyt.io

www.dolphindb.com

milvus.io

www.oracle.com/database

Technical documentation

docs.brytlyt.io

docs.dolphindb.cn/en/help200/index.html

milvus.io/docs/overview.md

docs.oracle.com/en/database

Developer

Brytlyt

DolphinDB, Inc

Oracle

Initial release

2016

2018

2019

1980

Current release

5.0, August 2023

v2.00.4, January 2022

2.3.4, January 2024

23c, September 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2.0

commercial

restricted free version is available

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, C++ and CUDA

C++

C++, Go

C and C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Schemaless in JSON and XML columns

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.

yes

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators, Users, Groups

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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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