DBMS > Atos Standard Common Repository vs. MaxDB vs. Milvus vs. Solr vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. MaxDB vs. Milvus vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A robust and reliable RDBMS optimized to run all major SAP solutions

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

A widely used distributed, scalable search engine based on Apache Lucene

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS

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

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

maxdb.sap.com

milvus.io

solr.apache.org

yaacomo.com

Technical documentation

maxdb.sap.com/documentation

milvus.io/docs/overview.md

solr.apache.org/resources.html

Developer

Atos Convergence Creators

SAP, acquired from Software AG (Adabas-D) in 1997

Apache Software Foundation

Q2WEB GmbH

Initial release

2016

1984

2019

2006

2009

Current release

1703

7.9.10.12, February 2024

2.3.4, January 2024

9.6.0, April 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2.0

Open Source

Apache Version 2

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

Java

C++

C++, Go

Java

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

optional

yes

Vector, Numeric and String

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Solr Parallel SQL Interface

yes

APIs and other access methods

LDAP

ADO.NET
JDBC
ODBC
WebDAV

RESTful HTTP API

Java API
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C#
Java
Perl
PHP
Python

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

optimistic locking

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

LDAP bind authentication

fine grained access rights according to SQL-standard

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

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

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