DBMS > Apache HBase vs. Milvus vs. TypeDB

System Properties Comparison Apache HBase vs. Milvus vs. TypeDB

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.

Primary database model

Wide column store

Vector DBMS

Graph DBMS

The type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS

The data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS

The type-theoretic data model of TypeDB subsumes the relational database model.

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

Score	24.08
Rank	#26	Overall
	#2	Wide column stores

Score	2.77
Rank	#91	Overall
	#7	Vector DBMS

Score	0.64
Rank	#229	Overall
	#20	Graph DBMS
	#8	Object oriented DBMS
	#106	Relational DBMS

Website

hbase.apache.org

milvus.io

typedb.com

Technical documentation

hbase.apache.org/book.html

milvus.io/docs/overview.md

typedb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Vaticle

Initial release

2008

2019

2016

Current release

2.3.4, January 2021

2.4.4, May 2024

2.28.3, June 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

GPL Version 3, commercial licenses 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.

Implementation language

Java

C++, Go

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

Data scheme

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

APIs and other access methods

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication via raft

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

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Role based access control and fine grained access rights

yes

at REST API level; other APIs in progress

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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