DBMS > Cachelot.io vs. Cassandra vs. EsgynDB vs. KeyDB vs. NSDb

System Properties Comparison Cachelot.io vs. Cassandra vs. EsgynDB vs. KeyDB vs. NSDb

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

cachelot.io

cassandra.apache.org

www.esgyn.cn

github.com/Snapchat/KeyDB
keydb.dev

nsdb.io

Technical documentation

cassandra.apache.org/doc/latest

docs.keydb.dev

nsdb.io/Architecture

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Esgyn

EQ Alpha Technology Ltd.

Initial release

2015

2008

2015

2019

2017

Current release

4.1.3, July 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache version 2

commercial

Open Source

BSD-3

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.

Implementation language

C++

Java

C++, Java

C++

Java, Scala

Server operating systems

FreeBSD
Linux
OS X

BSD
Linux
OS X
Windows

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes: int, bigint, decimal, 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

by using the Redis Search module

all fields are automatically indexed

SQL

Support of SQL

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

yes

SQL-like query language

APIs and other access methods

Memcached protocol

Proprietary protocol

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

ADO.NET
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Java
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual 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

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

Using Apache Lucene

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

simple password-based access control and ACL

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

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

Licensing and pricing models

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