DBMS > Manticore Search vs. OrigoDB vs. Riak KV vs. Sadas Engine vs. TerminusDB

System Properties Comparison Manticore Search vs. OrigoDB vs. Riak KV vs. Sadas Engine vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Search engine

Document store
Object oriented DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
RDF store

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

manual.manticoresearch.com

origodb.com/docs

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

terminusdb.github.io/terminusdb/#

Developer

Manticore Software

Robert Friberg et al

OpenSource, formerly Basho Technologies

SADAS s.r.l.

DataChemist Ltd.

Initial release

2017

2009

under the name LiveDB

2009

2006

2018

Current release

6.0, February 2023

3.2.0, December 2022

8.0

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version 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.

Implementation language

C++

Erlang

C++

Prolog, Rust

Server operating systems

FreeBSD
Linux
macOS
Windows

Linux
Windows

Linux
OS X

AIX
Linux
Windows

Linux

Data scheme

Fixed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

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

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

full-text index on all search fields

yes

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

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

.NET Client API
HTTP API
LINQ

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

.Net

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

Erlang

yes

Triggers

yes

Domain Events

yes

pre-commit hooks and post-commit hooks

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

client side managed; servers are not synchronized

Sharding

no "single point of failure"

horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Source-replica replication

selectable replication factor

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

links between data sets can be stored

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

Write ahead log

yes

in-memory journaling

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Role based authorization

yes, using Riak Security

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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