DBMS > Databricks vs. Manticore Search vs. RDF4J vs. Sadas Engine

System Properties Comparison Databricks vs. Manticore Search vs. RDF4J vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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.

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

Primary database model

Document store
Relational DBMS

Search engine

RDF store

Relational 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	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

Technical documentation

docs.databricks.com

manual.manticoresearch.com

rdf4j.org/documentation

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

Developer

Databricks

Manticore Software

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

SADAS s.r.l.

Initial release

2013

2017

2004

2006

Current release

6.0, February 2023

8.0

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

Fixed schema

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

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.

yes

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC
Proprietary protocol

Supported programming languages

Python
R
Scala

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

Java
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions and aggregates

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

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

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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