DBMS > Milvus vs. Oracle Berkeley DB vs. Teradata vs. TerarkDB vs. Transwarp StellarDB

System Properties Comparison Milvus vs. Oracle Berkeley DB vs. Teradata vs. TerarkDB vs. Transwarp StellarDB

Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

A hybrid cloud data analytics software platform (Teradata Vantage)

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Vector DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Website

milvus.io

www.oracle.com/database/technologies/related/berkeleydb.html

www.teradata.com

github.com/bytedance/terarkdb

www.transwarp.cn/en/product/stellardb

Technical documentation

milvus.io/docs/overview.md

docs.oracle.com/cd/E17076_05/html/index.html

docs.teradata.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Teradata

ByteDance, originally Terark

Transwarp

Initial release

2019

1994

1984

2016

Current release

2.3.4, January 2024

18.1.40, May 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial license available

commercial

restricted open source version available

commercial

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

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL 2016 + extensions

SQL-like query language

APIs and other access methods

RESTful HTTP API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

C++ API
Java API

OpenCypher

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Hashing

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

User concepts

Access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

yes

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

show all

Recent citations in the news

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, HPCwire

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

Oracle buys Sleepycat Software
14 February 2006, MarketWatch

provided by Google News

Is There Now An Opportunity In Teradata Corporation (NYSE:TDC)?
28 May 2024, Yahoo Finance

Should You Be Excited About Teradata Corporation's (NYSE:TDC) 78% Return On Equity?
27 May 2024, Simply Wall St

Teradata Co. (NYSE:TDC) Shares Purchased by Neuberger Berman Group LLC
28 May 2024, Defense World

Teradata takes plunge into lakehouse waters, but not everyone is convinced
23 May 2024, The Register

Teradata Asks 9th Circ. To Revive SAP Antitrust, IP Claims
12 February 2024, Law360

provided by Google News

Share this page