DBMS > Datastax Enterprise vs. DuckDB vs. KeyDB vs. NSDb

System Properties Comparison Datastax Enterprise vs. DuckDB vs. KeyDB vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.datastax.com/products/datastax-enterprise

duckdb.org

github.com/Snapchat/KeyDB
keydb.dev

nsdb.io

Technical documentation

Developer

DataStax

EQ Alpha Technology Ltd.

Initial release

2011

2018

2019

2017

Current release

6.8, April 2020

0.10, February 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

C++

Java, Scala

Server operating systems

Linux
OS X

server-less

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

yes

by using the Redis Search module

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

none

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

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual 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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

simple password-based access control and ACL

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» 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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

DataStax previews new Hyper Converged Data Platform for enterprise AI
15 May 2024, VentureBeat

DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite ...
15 May 2024, Business Wire

DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
19 July 2023, EnterpriseAI

DataStax announces vector search capabilities in its on-prem Apache Cassandra database
8 August 2023, SDTimes.com

DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers
20 February 2024, Business Wire

provided by Google News

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
20 September 2023, PR Newswire

provided by Google News

Oh, snap! Snap snaps up database developer KeyDB
12 May 2022, TechCrunch

Snap Acquires KeyDB for Open-Source Services
17 May 2022, XR Today

Garnet–open-source faster cache-store speeds up applications, services
18 March 2024, microsoft.com

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Microsoft open-sources Garnet cache-store -- a Redis rival?
19 March 2024, The Stack

provided by Google News

Share this page