DBMS > Badger vs. IBM Db2 Event Store vs. Milvus vs. SAP HANA

System Properties Comparison Badger vs. IBM Db2 Event Store vs. Milvus vs. SAP HANA

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store

Event Store
Time Series DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

github.com/dgraph-io/badger

www.ibm.com/products/db2-event-store

milvus.io

www.sap.com/products/hana.html

Technical documentation

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

www.ibm.com/docs/en/db2-event-store

milvus.io/docs/overview.md

help.sap.com/hana

Developer

DGraph Labs

IBM

SAP

Initial release

2017

2019

2010

Current release

2.0

2.4.4, May 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

C and C++

C++, Go

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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 access rights according to SQL-standard

Role based access control and fine grained access rights

yes

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.