DBMS > EXASOL vs. Machbase Neo vs. Manticore Search vs. RDF4J vs. Tigris

System Properties Comparison EXASOL vs. Machbase Neo vs. Manticore Search vs. RDF4J vs. Tigris

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

TimeSeries DBMS for AIoT and BigData

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Score	0.23
Rank	#317	Overall
	#21	Search engines

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.01
Rank	#388	Overall
	#53	Document stores
	#61	Key-value stores
	#25	Search engines
	#41	Time Series DBMS

Website

Technical documentation

www.exasol.com/resources

machbase.com/dbms

manual.manticoresearch.com

rdf4j.org/documentation

www.tigrisdata.com/docs

Developer

Exasol

Machbase

Manticore Software

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Tigris Data, Inc.

Initial release

2000

2013

2017

2004

2022

Current release

V8.0, August 2023

6.0, February 2023

License

Commercial or Open Source

commercial

free test version available

Open Source

GPL version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

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++

Java

Server operating systems

Linux
macOS
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

yes

Fixed schema

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

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

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

Java
Lua
Python
R

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Java
PHP
Python

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication based on Galera library

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Isolation support depends on the API used

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

in-memory storage is supported as well

yes, using FoundationDB

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

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

simple password-based access control

Access rights for users and roles

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