DBMS > LeanXcale vs. Manticore Search vs. MySQL vs. Quasardb

System Properties Comparison LeanXcale vs. Manticore Search vs. MySQL vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Widely used open source RDBMS

Distributed, high-performance timeseries database

Primary database model

Key-value store
Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

Technical documentation

manual.manticoresearch.com

dev.mysql.com/doc

doc.quasar.ai/master

Developer

LeanXcale

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

Initial release

2015

2017

1995

2009

Current release

6.0, February 2023

8.4.0, April 2024

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

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

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

through Apache Derby

SQL-like query language

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Supported programming languages

C
Java
Scala

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

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

ACID

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

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

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

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