DBMS > HarperDB vs. MySQL vs. NCache vs. Typesense

System Properties Comparison HarperDB vs. MySQL vs. NCache vs. Typesense

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Editorial information provided by DB-Engines

Name

Description

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Widely used open source RDBMS

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

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Search engine

Secondary database models

Document store
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

www.harperdb.io

www.mysql.com

www.alachisoft.com/ncache

typesense.org

Technical documentation

docs.harperdb.io/docs

dev.mysql.com/doc

www.alachisoft.com/resources/docs

typesense.org/docs

Developer

HarperDB

Oracle

since 2010, originally MySQL AB, then Sun

Alachisoft

Initial release

2017

1995

2005

2015

Current release

3.1, August 2021

8.4.0, April 2024

5.3.3, April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Enterprise Edition available

Open Source

GPL V3

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.

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Implementation language

Node.js

C and C++

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

dynamic schema

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

JSON data types

yes

partial

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

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

with proprietary extensions

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

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

proprietary syntax

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

not for MyISAM storage engine

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes, using LMDB

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 and roles

Users with fine-grained authorization concept

no user groups or roles

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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