DBMS > KeyDB vs. Kinetica vs. NCache vs. Riak TS

System Properties Comparison KeyDB vs. Kinetica vs. NCache vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

Open-Source and Enterprise in-memory Key-Value Store

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	0.25
Rank	#308	Overall
	#26	Time Series DBMS

Website

github.com/Snapchat/KeyDB
keydb.dev

www.kinetica.com

www.alachisoft.com/ncache

Technical documentation

docs.keydb.dev

docs.kinetica.com

www.alachisoft.com/resources/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

EQ Alpha Technology Ltd.

Kinetica

Alachisoft

Open Source, formerly Basho Technologies

Initial release

2019

2012

2005

2015

Current release

7.1, August 2021

5.3.3, April 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

BSD-3

commercial

Open Source

Enterprise Edition available

Open Source

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.

Implementation language

C++

C, C++

C#, .NET, .NET Core, Java

Erlang

Server operating systems

Linux

Linux
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

partial

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

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

yes

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes, limited

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP API
Native Erlang Interface

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Lua

user defined functions

support for stored procedures with SQL-Server CLR

Erlang

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Notifications

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes, with selectable consistency level

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

optimistic locking and pessimistic locking

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

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

simple password-based access control and ACL

Access rights for users and roles on table level

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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