DBMS > Cassandra vs. HBase vs. Milvus vs. OpenTSDB

System Properties Comparison Cassandra vs. HBase vs. Milvus vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

Scalable Time Series DBMS based on HBase

Primary database model

Wide column store

Vector DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

Technical documentation

cassandra.apache.org/doc/latest

hbase.apache.org/book.html

milvus.io/docs/overview.md

opentsdb.net/docs/build/html/index.html

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation

Apache top-level project, originally developed by Powerset

currently maintained by Yahoo and other contributors

Initial release

2008

2019

2011

Current release

4.1.3, July 2023

2.3.4, January 2021

2.4.4, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

LGPL

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++, Go

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

Vector, Numeric and String

numeric data for metrics, strings for tags

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

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency or Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

Single row ACID (across millions of columns)

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 rights for users can be defined per object

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

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Milvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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News

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11 June 2024

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7 June 2024

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3 June 2024

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30 May 2024

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