DBMS > Google BigQuery vs. InterSystems Caché vs. Milvus vs. Newts vs. Oracle Rdb

System Properties Comparison Google BigQuery vs. InterSystems Caché vs. Milvus vs. Newts vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

A multi-model DBMS and application server

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

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Vector DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

cloud.google.com/bigquery

www.intersystems.com/products/cache

milvus.io

opennms.github.io/newts

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

Technical documentation

cloud.google.com/bigquery/docs

docs.intersystems.com

milvus.io/docs/overview.md

github.com/OpenNMS/newts/wiki

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Google

InterSystems

OpenNMS Group

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2010

1997

2019

2014

1984

Current release

2018.1.4, May 2020

2.3.4, January 2024

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

HP Open VMS

Data scheme

yes

depending on used data model

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP REST
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java

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

Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes, on a single node

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)

Access rights for users, groups and roles

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...
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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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