DBMS > Manticore Search vs. OrientDB vs. SQLite vs. Trino

System Properties Comparison Manticore Search vs. OrientDB vs. SQLite vs. Trino

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Editorial information provided by DB-Engines

Name

Description

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

Multi-model DBMS (Document, Graph, Key/Value)

Widely used embeddable, in-process RDBMS

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Search engine

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

Technical documentation

manual.manticoresearch.com

www.orientdb.com/docs/last/index.html

www.sqlite.org/docs.html

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Manticore Software

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Trino Software Foundation

Initial release

2017

2010

2000

2012

2020 rebranded from PrestoSQL

Current release

6.0, February 2023

3.2.29, March 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

Apache version 2

Open Source

Public Domain

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS
Windows

All OS with a Java JDK (>= JDK 6)

server-less

Linux
macOS

for devlopment

Data scheme

Fixed schema

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

dynamic column types

yes

Typing

predefined data types such as float or date

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

yes

not rigid because of 'dynamic typing' concept.

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

depending on connected data-source

SQL

Support of SQL

SQL-like query language

SQL-like query language, no joins

yes

SQL-92 is not fully supported

yes

APIs and other access methods

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

Java, Javascript

yes, depending on connected data-source

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Multi-source replication

none

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

depending on connected data-source

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

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

yes

depending on connected data-source

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; record level security configurable

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

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Key customers

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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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