DBMS > EJDB vs. Kdb vs. Milvus vs. Newts vs. STSdb

System Properties Comparison EJDB vs. Kdb vs. Milvus vs. Newts vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

High performance Time Series DBMS

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

Time Series DBMS based on Cassandra

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

Time Series DBMS
Vector DBMS

Vector DBMS

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/Softmotions/ejdb

kx.com

milvus.io

opennms.github.io/newts

github.com/STSSoft/STSdb4

Technical documentation

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

code.kx.com

milvus.io/docs/overview.md

github.com/OpenNMS/newts/wiki

Developer

Softmotions

Kx Systems, a division of First Derivatives plc

OpenNMS Group

STS Soft SC

Initial release

2012

2000

kdb was released 2000, kdb+ in 2003

2019

2014

2011

Current release

3.6, May 2018

2.3.4, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

GPLv2

commercial

free 32-bit version

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license 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++, Go

Java

Server operating systems

server-less

Linux
OS X
Solaris
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

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

yes

primitive types and user defined types (classes)

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

yes

table attribute 'grouped'

SQL

Support of SQL

SQL-like query language (q)

APIs and other access methods

in-process shared library

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP API

HTTP REST
Java API

.NET Client API

Supported programming languages

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

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

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

Java

C#
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

rights management via user accounts

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

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

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

upon request
» more

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.

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