DBMS > HarperDB vs. Manticore Search vs. MariaDB vs. Qdrant vs. Sphinx

System Properties Comparison HarperDB vs. Manticore Search vs. MariaDB vs. Qdrant vs. Sphinx

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.

Multi-storage database for search, including full-text search.

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

A high-performance vector database with neural network or semantic-based matching

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.harperdb.io

manticoresearch.com

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

github.com/qdrant/qdrant
qdrant.tech

sphinxsearch.com

Technical documentation

docs.harperdb.io/docs

manual.manticoresearch.com

mariadb.com/kb/en/library

qdrant.tech/documentation

sphinxsearch.com/docs

Developer

HarperDB

Manticore Software

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Qdrant

Sphinx Technologies Inc.

Initial release

2017

2009

Fork of MySQL, which was first released in 1995

2021

2001

Current release

3.1, August 2021

6.0, February 2023

11.3.2, February 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPL version 2

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

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

Node.js

C++

C and C++

Rust

C++

Server operating systems

Linux
OS X

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Docker
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

dynamic schema

Fixed schema

yes

Dynamic columns are supported

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

Numbers, Strings, Geo, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

Keywords, numberic ranges, geo, full-text

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query language

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Proprietary protocol

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

user defined functions

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Partitioning is done manually, search queries against distributed index is supported

several options for horizontal partitioning and Sharding

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

yes

The original contents of fields are not stored in the Manticore index.

yes

not for in-memory storage engine

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Market metrics

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Licensing and pricing models

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