DBMS > Atos Standard Common Repository vs. Badger vs. BigchainDB vs. Milvus vs. Riak TS

System Properties Comparison Atos Standard Common Repository vs. Badger vs. BigchainDB vs. Milvus vs. Riak TS

Editorial information provided by DB-Engines

Name

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

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Key-value store

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

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

github.com/dgraph-io/badger

www.bigchaindb.com

milvus.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

bigchaindb.readthedocs.io/en/latest

milvus.io/docs/overview.md

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Atos Convergence Creators

DGraph Labs

Open Source, formerly Basho Technologies

Initial release

2016

2017

2016

2019

2015

Current release

1703

2.3.4, January 2024

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

AGPL v3

Open Source

Apache Version 2.0

Open Source

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

Python

C++, Go

Erlang

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

yes, limited

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

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...
» 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

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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