DBMS > Badger vs. Faircom EDGE vs. Milvus vs. Teradata Aster

System Properties Comparison Badger vs. Faircom EDGE vs. Milvus vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Key-value store

Key-value store
Relational DBMS

Vector DBMS

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Website

github.com/dgraph-io/badger

www.faircom.com/products/faircom-edge

milvus.io

Technical documentation

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

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

milvus.io/docs/overview.md

Developer

DGraph Labs

FairCom Corporation

Teradata

Initial release

2017

1979

2019

2005

Current release

V3, October 2020

2.4.4, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

Apache Version 2.0

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

ANSI C, C++

C++, Go

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

Data scheme

schema-free

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Role based access control and fine grained access rights

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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