DBMS > BaseX vs. Couchbase vs. Google Cloud Spanner vs. Microsoft Access vs. Milvus

System Properties Comparison BaseX vs. Couchbase vs. Google Cloud Spanner vs. Microsoft Access vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	18.46
Rank	#36	Overall
	#5	Document stores

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Website

basex.org

www.couchbase.com

cloud.google.com/spanner

www.microsoft.com/en-us/microsoft-365/access

milvus.io

Technical documentation

docs.basex.org

docs.couchbase.com

cloud.google.com/spanner/docs

developer.microsoft.com/en-us/access

milvus.io/docs/overview.md

Developer

BaseX GmbH

Couchbase, Inc.

Google

Microsoft

Initial release

2007

2011

2017

1992

2019

Current release

10.7, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1902 (16.0.11328.20222), March 2019

2.3.4, January 2024

License

Commercial or Open Source

Open Source

BSD license

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Bundled with Microsoft Office

Open Source

Apache Version 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

Java

C, C++, Go and Erlang

C++

C++, Go

Server operating systems

Linux
OS X
Windows

hosted

Windows

Not a real database server, but making use of DLLs

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

Vector, Numeric and String

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++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

Query statements complying to ANSI 2011

yes

but not compliant to any SQL standard

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

since Access 2010 using the ACE-engine

Triggers

yes

via events

yes

via the TAP protocol

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Strict serializable isolation

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

a simple user-level security was built in till version Access 2003

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...
» more

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....
» 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...
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