DBMS > Cassandra vs. EsgynDB vs. etcd vs. EXASOL vs. Milvus

System Properties Comparison Cassandra vs. EsgynDB vs. etcd vs. EXASOL vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A distributed reliable key-value store

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

cassandra.apache.org

www.esgyn.cn

etcd.io
github.com/etcd-io/etcd

www.exasol.com

milvus.io

Technical documentation

cassandra.apache.org/doc/latest

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.exasol.com/resources

milvus.io/docs/overview.md

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Esgyn

Exasol

Initial release

2008

2015

2000

2019

Current release

4.1.3, July 2023

3.4, August 2019

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0

commercial

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.

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

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++, Java

C++, Go

Server operating systems

BSD
Linux
OS X
Windows

Linux

FreeBSD
Linux
Windows

experimental

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

yes

APIs and other access methods

Proprietary protocol

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

ADO.NET
JDBC
ODBC

gRPC
JSON over HTTP

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java
Lua
Python
R

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

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication between multi datacenters

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

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 rights for users can be defined per object

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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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