DBMS > Google BigQuery vs. Milvus vs. ObjectBox vs. Trafodion

System Properties Comparison Google BigQuery vs. Milvus vs. ObjectBox vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Vector DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Website

cloud.google.com/bigquery

milvus.io

github.com/objectbox
objectbox.io

trafodion.apache.org

Technical documentation

cloud.google.com/bigquery/docs

milvus.io/docs/overview.md

docs.objectbox.io

trafodion.apache.org/documentation.html

Developer

Google

ObjectBox Limited

Apache Software Foundation, originally developed by HP

Initial release

2010

2019

2017

2014

Current release

2.4.4, May 2024

4.0 (May 2024)

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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 and C++

C++, Java

Server operating systems

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes, plus "flex" map-like types

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Data sync between devices allowing occasional connected databases to work completely offline

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

Since BigQuery is designed for querying 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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role based access control and fine grained access rights

yes

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

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.