DBMS > Datastax Enterprise vs. DuckDB vs. Milvus vs. STSdb

System Properties Comparison Datastax Enterprise vs. DuckDB vs. Milvus vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	4.82
Rank	#65	Overall
	#4	Wide column stores

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

www.datastax.com/products/datastax-enterprise

duckdb.org

milvus.io

github.com/STSSoft/STSdb4

Technical documentation

docs.datastax.com

duckdb.org/docs

milvus.io/docs/overview.md

Developer

DataStax

STS Soft SC

Initial release

2011

2018

2019

2011

Current release

6.8, April 2020

1.0.0, June 2024

2.4.4, May 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++

C++, Go

Server operating systems

Linux
OS X

server-less

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP API

.NET Client API

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

C#
Java

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users can be defined per object

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

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

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

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

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

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

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

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

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

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

Licensing and pricing models

Annual subscription
» 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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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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