DBMS > Machbase Neo vs. Manticore Search vs. RavenDB vs. RDF4J vs. SAP SQL Anywhere

System Properties Comparison Machbase Neo vs. Manticore Search vs. RavenDB vs. RDF4J vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

TimeSeries DBMS for AIoT and BigData

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

machbase.com/dbms

manual.manticoresearch.com

ravendb.net/docs

rdf4j.org/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Machbase

Manticore Software

Hibernating Rhinos

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

SAP

formerly Sybase

Initial release

2013

2017

2010

2004

1992

Current release

V8.0, August 2023

6.0, February 2023

5.4, July 2022

17, July 2015

License

Commercial or Open Source

commercial

free test version available

Open Source

GPL version 2

Open Source

AGPL version 3, commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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
macOS
Raspberry Pi
Windows

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Fixed schema

schema-free

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

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (RQL)

yes

APIs and other access methods

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

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

yes, in C/C++, Java, .Net or Perl

Triggers

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication based on Galera library

Multi-source replication

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

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, Cluster-wide transaction available

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

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

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