DBMS > EJDB vs. Infobright vs. Kingbase vs. Microsoft SQL Server vs. Milvus

System Properties Comparison EJDB vs. Infobright vs. Kingbase vs. Microsoft SQL Server vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Microsofts flagship relational DBMS

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

Primary database model

Document store

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Website

github.com/Softmotions/ejdb

ignitetech.com/softwarelibrary/infobrightdb

www.kingbase.com.cn

www.microsoft.com/en-us/sql-server

milvus.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

learn.microsoft.com/en-US/sql/sql-server

milvus.io/docs/overview.md

Developer

Softmotions

Ignite Technologies Inc.; formerly InfoBright Inc.

BeiJing KINGBASE Information technologies inc.

Microsoft

Initial release

2012

2005

1999

1989

2019

Current release

V8.0, August 2021

SQL Server 2022, November 2022

2.3.4, January 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

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

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C and Java

C++

C++, Go

Server operating systems

server-less

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

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.

yes

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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....
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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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