DBMS > Cassandra vs. ClickHouse vs. Elasticsearch vs. Graph Engine vs. Milvus

System Properties Comparison Cassandra vs. ClickHouse vs. Elasticsearch vs. Graph Engine vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Wide column store

Relational DBMS

Search engine

Graph DBMS
Key-value store

Vector DBMS

Secondary database models

Vector DBMS

starting with release V5

Time Series DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

cassandra.apache.org

clickhouse.com

www.elastic.co/elasticsearch

www.graphengine.io

milvus.io

Technical documentation

cassandra.apache.org/doc/latest

clickhouse.com/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.graphengine.io/docs/manual

milvus.io/docs/overview.md

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Clickhouse Inc.

Elastic

Microsoft

Initial release

2008

2016

2010

2019

Current release

4.1.3, July 2023

v24.3.2.23-lts, April 2024

8.6, January 2023

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Elastic License

Open Source

MIT License

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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++

Java

.NET and C

C++, Go

Server operating systems

BSD
Linux
OS X
Windows

FreeBSD
Linux
macOS

All OS with a Java VM

.NET

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

SQL

Support of SQL

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

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

APIs and other access methods

Proprietary protocol

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

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

key based and custom

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users can be defined per object

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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...
» more

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

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.