DBMS > GeoMesa vs. IBM Db2 Event Store vs. Milvus vs. ObjectBox vs. STSdb

System Properties Comparison GeoMesa vs. IBM Db2 Event Store vs. Milvus vs. ObjectBox vs. STSdb

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Distributed Event Store optimized for Internet of Things use cases

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

Extremely fast embedded database for small devices, IoT and Mobile

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Spatial DBMS

Event Store
Time Series DBMS

Vector DBMS

Object oriented DBMS

Key-value store

Secondary database models

Time Series DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.geomesa.org

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

milvus.io

objectbox.io

github.com/STSSoft/STSdb4

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

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

milvus.io/docs/overview.md

docs.objectbox.io

Developer

CCRi and others

IBM

ObjectBox Limited

STS Soft SC

Initial release

2014

2017

2019

2017

2011

Current release

4.0.5, February 2024

2.0

2.3.4, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free developer edition available

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

GPLv2, commercial license available

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

Scala

C and C++

C++, Go

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Android
iOS
Linux
macOS
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

primitive types and user defined types (classes)

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

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Proprietary native API

.NET Client API

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Active-active shard replication

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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

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