DBMS > Axibase vs. Badger vs. BigObject vs. EventStoreDB vs. Milvus

System Properties Comparison Axibase vs. Badger vs. BigObject vs. EventStoreDB vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

Analytic DBMS for real-time computations and queries

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Event Store

Vector DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

axibase.com/docs/atsd/finance

github.com/dgraph-io/badger

bigobject.io

www.eventstore.com

milvus.io

Technical documentation

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

docs.bigobject.io

developers.eventstore.com

milvus.io/docs/overview.md

Developer

Axibase Corporation

DGraph Labs

BigObject, Inc.

Event Store Limited

Initial release

2013

2017

2015

2012

2019

Current release

15585

21.2, February 2021

2.3.4, January 2024

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0

commercial

free community edition available

Open Source

Apache Version 2.0

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++, Go

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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

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

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More resources

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